Machine Learning Engineer, Lyft Business

🏢 Summary: Senior engineer role focused on designing and implementing evaluation frameworks for large ML models powering autonomous driving systems. The position centers on developing metrics, simulation strategies, and data pipelines to rigorously assess model performance and safety at scale. The role involves close collaboration with ML and research teams to translate quantitative insights into production-ready evaluation tools. 🗂️ Requirements: 7+ years industry experience in quantitative software engineering, Proficiency in Python or C++, Experience with software design principles and testing methodologies, Experience with version control systems, Experience building large-scale data processing or evaluation pipelines, Strong knowledge of AI fundamentals including transformer architectures, Experience evaluating machine learning models, Experience productionizing quantitative tools, Ability to define technical strategy and roadmaps 📃 Skills: Python, C++, MachineLearning, Transformers, Simulation, DataPipelines, DataAnalysis, JAX, TensorFlow, VersionControl, Testing, Robotics 🏢 Description: Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.The Large Model Evaluation team is at the nexus of Waymo’s AI ambition. With advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs), Waymo is building state-of-the-art AI systems that handle the full complexity of real-world driving. At its core, our progress is defined by our ability to measure it. While robust evaluation is the bottleneck for deploying any large model, the challenge at Waymo is uniquely complex and safety-critical. We are looking for quantitatively-minded engineers to research and propose new ways to assess the ML models deployed in the Waymo Driver. You will: Develop novel metrics and sampling techniques to measure the driving trajectories generated by ML models. Employ creative simulation strategies to measure the driving performance of generative AI models. Identify potential edge cases, and provide reliable performance insights that inform model development and deployment. Build data pipelines for signal discovery, data labeling, feature extraction and metric computation based on large-scale simulations. Conduct data analysis to diagnose regressions in ML models. Collaborate with world-class engineering and research teams that develop large-scale ML models. You have: 7+ years of relevant industry experience in a heavily quantitative software engineering area Experience navigating complex technical and product landscapes, defining technical strategy, and creating roadmaps. Software Engineering Fundamentals: Proficiency in programming in Python or C++ Experience with software design principles, coding best practices, testing methodologies, and version control software. Experience building software pipelines for data processing, system evaluation, or metric computation, in the context of large-scale systems. Machine learning & Quantitative Experience Knowledge of AI fundamentals, such as transformer architectures, distillation techniques, etc. Experience evaluating the quality of ML models Demonstrated experience taking quantitative findings through to productionized tools. We prefer: Experience with simulation systems, robotics, or autonomous vehicles. Familiarity with one of the modern deep learning frameworks (e.g. JAX, Tensorflow) Experience leading a team of Engineers The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range$238,000—$302,000 USD

🏢 Summary: The offer is for a Software Engineer (Agent Development) role focused on building and scaling production-ready AI agents and autonomous marketing workflows. The position combines strong backend engineering with applied GenAI, emphasizing reliable, scalable systems integrated into a live marketing automation platform. The role involves working with LLM orchestration, backend services, and AI-driven integrations in a fast-paced, collaborative environment. 🗂️ Requirements: 2–4 years of software engineering experience, Strong experience in Python and scalable backend development, Understanding of building production-ready, maintainable systems, Interest in AI, GenAI, and agentic systems, Experience with backend databases such as MySQL, Redis, or DynamoDB, Ability to work in fast-paced, iterative environments, Strong problem-solving skills, Ability to collaborate with cross-functional and distributed teams 📃 Skills: Python, GenAI, LLM, MySQL, Redis, DynamoDB, APIs, CI/CD, Cloud, AI, Agents 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Agent Development) to join our client’s growing AI team and help build the next generation of autonomous AI agents powering modern marketing workflows. In this role, you’ll work at the intersection of backend engineering and applied AI, designing and scaling production-ready agentic systems used by businesses worldwide. This is not a pure research role. The focus is on strong software engineering fundamentals and building reliable, scalable AI-powered products. You’ll work across backend systems, orchestration, integrations, and AI workflows, collaborating closely with cross-functional product and engineering teams. The environment is fast-paced and highly collaborative, with a strong emphasis on ownership, rapid iteration, and building real-world AI solutions already running in production. Key takeaways: Stack: Python, AI Agents, MySQL, GenAI Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Technical interview, live coding (1h) Cross-functional interview (1h) Interview with Hiring Manager (45 min) | Optional Responsibilities: Design and develop production-grade AI agents and autonomous marketing workflows across the platform. Build and maintain multi-step agentic systems involving LLM orchestration, tool usage, and backend integrations. Work with LLM APIs, including prompt engineering, response handling, evaluation, and optimization of AI workflows. Create and improve evaluation frameworks, quality metrics, and monitoring processes to ensure agent reliability and performance at scale. Monitor and optimize agent behavior, latency, token usage, cost efficiency, and production stability. Develop production-quality backend services and orchestration layers primarily using Python. Contribute to backend and frontend integration points where AI agents interact with the core platform. Build and maintain APIs, service interfaces, and data flows supporting AI-driven capabilities. Collaborate closely with Product, Design, and Engineering teams to define and deliver AI-powered user experiences. Ensure code quality through testing, code reviews, and adherence to engineering best practices. Participate in on-call rotations supporting AI agent services and platform reliability. Contribute to technical documentation, architectural decisions, and AI engineering best practices. Collaborate closely with globally distributed teams, including regular overlap with US-based stakeholders. Requirements: 2–4 years of experience in software engineering, with strong backend development fundamentals. Strong hands-on experience with Python and building scalable backend services. Interest in AI, GenAI, and agentic systems, with a willingness to grow in this area professionally. Exposure to AI-related projects, LLM-based solutions, ML models, or personal AI experiments is considered a strong plus. Understanding of how to build reliable, maintainable, and production-ready systems. Ability to work in fast-paced, iterative environments and ship code quickly while maintaining engineering quality. Familiarity with modern backend and database technologies such as MySQL, Redis, or DynamoDB. Strong problem-solving skills and the ability to work across different systems and technologies. Experience with cloud environments, APIs, CI/CD practices, or observability tooling is a plus. Familiarity with AI agent frameworks, prompt engineering, or LLM workflows is nice to have, but not required. Strong communication skills and a collaborative mindset within cross-functional engineering teams. Willingness to collaborate with globally distributed teams, including regular overlap with US-based stakeholders. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.

🏢 Summary: Machine Learning Engineer II role focused on designing, building, and deploying production-grade machine learning models that improve core product experiences and drive measurable business impact. The position emphasizes modeling, experimentation, and close collaboration with cross-functional teams to bring scalable ML solutions into high-traffic user flows. This is an individual contributor role centered on algorithmic innovation and end-to-end ML lifecycle ownership. 🗂️ Requirements: BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or related field, 2+ years of industry experience in machine learning, software engineering, data science, or related field, Strong knowledge of data structures, algorithms, and software design, Experience building or operating ML or AI systems, Proficiency in Python, Proficiency in at least one of: Java, Kotlin, Go, Scala, Strong understanding of model training, evaluation, and experimentation, Ability to design and analyze offline evaluations and online experiments, Experience writing production-quality code 📃 Skills: Python, Java, Kotlin, Go, Scala, Spark, Flink, AWS, Kubernetes, TensorFlow, TorchServe, Triton, Ray, Airflow, CI/CD, MLOps 🏢 Description: Our Mission As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing. We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more. Our Values Take the Lead: We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down. Move Fast: We have a bias for action and urgency. Something that could be done tomorrow would be better if done today. Better Together: We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate. Real Talk: We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same. Safety First: We act with integrity, transparency, and consistency so people feel safe—whether they're swiping, matching, or working alongside us. Spark Fun: We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters. The Team or Role: The Tinder ML team drives impact across nearly every core domain of the product — Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue optimization. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder’s ecosystem. ML at Tinder is organized into three groups with distinct roles: Machine Learning Engineers who focus on modeling and algorithmic innovation (this role) Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training, serving, and feature management Machine Learning Software Engineers who bridge the gap between research and production by delivering machine learning models into real-world product experiences at scale About the Role We are looking for a Machine Learning Engineer II to help build and ship machine learning systems that improve product experience and drive measurable business impact. This role is ideal for an engineer with a strong foundation in machine learning and software engineering who is excited to work on real-world problems, partner cross-functionally, and grow quickly in a high-impact environment. This is an individual contributor role focused on modeling and algorithmic innovation. You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from development into production. The team’s work directly translates into measurable business outcomes, and many of its models are embedded in core Tinder user flows at scale. Where You'll Work: This is a hybrid role and requires in-office collaboration three times per week in Palo Alto, California. In this role, you will: Translate product and business problems into clear machine learning problems with measurable success criteria Build, train, evaluate, and improve production machine learning models Partner with software engineers and ML infrastructure engineers to deploy models and improve reliability, scalability, and performance in production Design and analyze offline evaluations and online experiments to understand model impact Contribute to feature engineering, data preparation, training pipelines, and model monitoring Write clean, maintainable, production-quality code and participate in design and code reviews Communicate technical findings, trade-offs, and recommendations clearly to both technical and non-technical partners You'll need: BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field 2+ years of industry experience in machine learning, software engineering, data science, or a related field Strong foundation in computer science fundamentals, including data structures, algorithms, and software design Experience building ML or AI-related systems, or strong understanding of how modern machine learning systems are developed and operated Proficiency in Python and at least one additional programming language such as Java, Kotlin, Go, Scala, or a similar language Strong understanding of machine learning fundamentals, including model training, evaluation, and experimentation Strong communication skills and the ability to collaborate effectively across functions Self-motivated, proactive, and comfortable taking ownership of well-scoped problems Nice to have: Experience with recommendation systems or casual inference Familiarity with big data or stream processing frameworks such as Spark or Flink Familiarity with cloud platforms such as AWS and containerized environments such as Kubernetes Familiarity with ML model serving frameworks such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray Serve Experience with feature stores, ML data pipelines, and orchestration frameworks such as Airflow Understanding of MLOps practices including CI/CD for ML, model versioning, and automated evaluation Exposure to observability and monitoring for ML systems Exposure to LLM-related use cases or applied generative AI projects As a full-time employee, you’ll enjoy: Flexible Vacation, 10 Sick Days Time off to volunteer and charitable donations matched up to $15,000 annually Comprehensive health, vision, and dental coverage 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP) 100% paid parental leave (including for non-birthing parents) and family forming benefits Investment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual $3,000 stipend for your professional development Investment in your wellness: access to mental health support via Modern Health, paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy Free subscription to Tinder Gold Commitment to Inclusion At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei

🏢 Summary: Senior LLM Systems Performance Engineer role focused on building and analyzing large-scale AI environments, optimizing LLM workloads, and driving hardware–software co-design for next-generation AI platforms. The position involves performance characterization across compute, memory, networking, and accelerator systems using modern AI frameworks and NVIDIA GPU platforms. Daily onsite presence in San Jose, CA is required. 🗂️ Requirements: MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field, BS with 5+ years of experience in performance engineering, AI systems, distributed systems, or HPC, Strong understanding of LLM inference and training systems, Strong understanding of NVIDIA GPU architecture and performance characteristics, Hands-on experience profiling and optimizing AI workloads on NVIDIA GPU platforms, Experience analyzing large-scale distributed AI workloads, Proficiency in Python, Proficiency in C++, Experience with modern AI frameworks or serving systems, Strong analytical and problem-solving skills, Ability to work onsite in San Jose, CA 📃 Skills: Python, C++, PyTorch, vLLM, SGLang, TensorRT-LLM, DeepSpeed, Ray, Megatron-LM, NVIDIA, Nsight, GPU, LLM, HPC 🏢 Description: Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World's Technology Together Our technology solutions power the tools you use every day—including smartphones, electric vehicles, hyperscale data centers, IoT devices, and more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. The team designs and develops scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. The lab collaborates closely with hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of systems. This role is offered by the STG group within the AGI Lab as part of DSRA. The team works at the intersection of large language models, accelerator hardware, and high-performance software. The mission is to design, prototype, and optimize next-generation AI systems through tight hardware–software co-design. We are seeking a Senior LLM Systems Performance Engineer to build representative AI environments, characterize emerging workloads, and drive performance analysis for next-generation AI platforms. In this role, you will set up and operate realistic LLM serving and agentic AI environments, collect workload traces and performance data, and develop methodologies to characterize workload behavior. Location: Daily onsite presence at the San Jose, CA office in alignment with the Flexible Work policy. Quick Facts What You'll Do - Build and operate representative AI environments, including agentic workflows, distributed inference systems, disaggregated serving architectures, and MoE deployments. - Collect workload traces, telemetry, and performance data from real-world AI applications. - Characterize workload behavior, develop representative benchmarks, and identify performance bottlenecks across compute, memory, communication, and scheduling resources. - Evaluate AI systems across the full hardware and software stack. - Analyze the impact of runtime, memory hierarchy, interconnect, and accelerator architecture on application performance. - Collaborate with hardware and software teams to drive performance analysis, architecture exploration, and hardware–software co-design for next-generation AI platforms. What You Bring - MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field. - BS with 5+ years of experience in performance engineering, AI systems, distributed systems, high-performance computing, or related areas. - Strong understanding of LLM inference and training systems. - Strong understanding of NVIDIA GPU architecture and performance characteristics. - Hands-on experience profiling and optimizing AI workloads on NVIDIA GPU platforms using Nsight Systems, Nsight Compute, and related frameworks. - Experience analyzing performance of large-scale distributed AI workloads. - Proficiency in Python and C++. - Experience with AI frameworks or serving systems such as PyTorch, vLLM, SGLang, TensorRT-LLM, DeepSpeed, Ray, or Megatron-LM. - Strong analytical and problem-solving skills. What We Offer - Competitive base pay range: $138,000—$206,000 USD. - Incentive opportunities based on individual and company performance. - Medical, Dental, Vision, and 401(k) benefits. - 4+ weeks of paid time off plus holidays and sick leave. - Family support benefits including fertility care, adoption assistance, and medical travel support. - Emotional wellness support including confidential therapy sessions. - Onsite café and gym with additional virtual wellness classes. - Flexible work environment. Equal Opportunity Employment Policy Samsung Semiconductor is committed to fostering an inclusive and equal opportunity workplace. Our Commitment to Innovation and Fairness AI tools may be used to support the recruitment process, but hiring decisions are made by human recruiters and hiring managers. Applicant AI Use Policy Generative AI tools may not be used to misrepresent candidate qualifications during the application or interview process. Trade Secret Notice By submitting an application, candidates agree not to disclose confidential or proprietary information belonging to current or former employers.

🏢 Summary: Machine Learning Engineer role focused on building statistical models and production systems for mobile ad tech economics, optimization, and advertiser performance. The position involves experimentation, bidding innovation, and collaboration across engineering and business teams in a remote-first environment. 🗂️ Requirements: PhD in Computer Science, Machine Learning, Economics, or related field, Industry experience applying economics or machine learning at large scale, Solid engineering and coding skills, Excellent communication and collaboration skills 📃 Skills: Python, MachineLearning, Statistics, Economics, Optimization, Experimentation, AdTech, Modeling, Coding 🏢 Description: About the Revenue Engine team The Revenue Engine team works to understand the fundamental economics of the mobile ad tech marketplace, including the elasticity of demand and the effects of competition. The team of machine learning engineers, software engineers, and data analysts develops theories, validates those theories with experiments and analyses, and uses the learnings to build production systems that improve outcomes for advertisers. As a Machine Learning Engineer on the Revenue Engine team, you will: - Build statistical models and production systems to balance advertiser performance with business goals. - Tune optimization parameters, measure internal competition, and model dynamic environments. - Design and run experiments to validate theories underpinning the mobile ad tech economy. - Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations. - Collaborate with engineers and peers across Operations and GTM teams. - Use strong communication skills to explain statistical and machine learning concepts to technical and non-technical audiences. - Contribute to an engineering excellence culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review. Requirements: - PhD in Computer Science, Machine Learning, Economics, or a related field. - Industry experience applying economics or machine learning to large scale problems. - Solid engineering and coding skills. - Excellent team communication and collaboration skills. - Experience with ad tech is a plus. Location: The preferred location for this role is within California. The company is remote-first with US hubs in Redwood City, Los Angeles, and New York City. Travel Expectations: Employees are expected to attend in-person gatherings, including project meetings, regional meetups, and company-wide events, at least once per quarter. Compensation: The compensation package includes equity and health, vision, and dental benefits associated with the employee's country of residence. Base compensation varies by location and experience. Base salary ranges: - SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $235,000 - $275,000 - All other approved states: $215,000 - $255,000 Benefits may include medical coverage, wellness stipends, and additional perks based on country of residence.

🏢 Summary: Machine Learning Engineer role focused on building and scaling ML-powered data mining pipelines for multimodal autonomous driving data, leveraging foundation models to discover rare edge cases and improve model performance. The position involves training and deploying models, developing embedding-based search and active learning workflows, and supporting production monitoring. You will collaborate across teams to translate ML prototypes into scalable, production-ready systems. 🗂️ Requirements: BS or MS in Computer Science, Machine Learning, or related field, Hands-on experience with PyTorch, TensorFlow, or JAX, Strong proficiency in Python, Experience with SQL and large-scale datasets, Proficiency with Pandas and NumPy, Knowledge of version control and unit testing, Understanding of full ML lifecycle from data preparation to deployment 📃 Skills: Python, PyTorch, TensorFlow, JAX, SQL, Pandas, NumPy, LiDAR, CI/CD, Git 🏢 Description: Mission Summary:At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional's driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation. What You'll Do: Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval. Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments. Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios. Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services. Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation. Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions. What We're Looking For (Must-Haves): BS or MS in Computer Science, Machine Learning, or a related field. Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics. Strong proficiency in Python with the ability to write clean, modular, and well-documented code. Working knowledge of version control, unit testing, and basic software design patterns. Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy. A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics. A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment. Bonus Points (Nice-to-Haves): MS/PhD in Computer Science, Machine Learning, or related field. Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning. Background in autonomous driving, robotics, or real-time decision-making systems. Familiarity with multimodal learning, sensor fusion, or embodied AI. Experience building active learning loops, using the model to find the data that breaks the model. Experience with ML-based data mining, active learning, or contrastive learning. Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms. Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV) We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.Salary Range$144,000—$192,000 USDMotional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more. Our journey is always people first. We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move. Higher purpose, greater impact. We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do. Scale up, not starting up. Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges. Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube. Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

🏢 Summary: Staff Software Engineer AI/ML role focused on building and productionizing agentic AI systems and next-generation ML/LLM solutions. The position involves designing, fine-tuning, and deploying large-scale models, integrating them into autonomous workflows, and driving experimentation to deliver scalable, reliable AI capabilities. Daily onsite collaboration with cross-functional engineering teams to develop generative and agentic AI frameworks. 🗂️ Requirements: MS or PhD in Computer Science, Electrical Engineering, or related field with ML focus, 4+ years experience in machine learning role, Strong research background in machine learning, computer vision, or natural language processing, Hands-on experience training or fine-tuning large-scale ML or LLM models, Experience with PyTorch or TensorFlow, Experience building and productionizing end-to-end ML systems, Proficiency in Python 📃 Skills: Python, PyTorch, TensorFlow, MachineLearning, DeepLearning, LLM, NLP, ComputerVision, MLOps, GenerativeAI 🏢 Description: Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. Advancing the World's Technology Together Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities.Staff Software Engineer AI/ML Samsung DSA has launched a new AI initiative to build the foundational capabilities for practical, agentic AI systems. The AI Innovation team is the driving force behind this vision, leading innovation at the intersection of machine learning and system engineering to develop and operate our next-generation Agentic AI framework. We aim to enable LLMs to autonomously plan, retrieve information, coordinate with tools, and execute multi-step workflows across our internal knowledge ecosystem. We are actively seeking talented Machine Learning Engineers specializing in building next-generation AI/ML solutions. Location: Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy What You'll Do Collaborate with cross-functional teams of engineers and architects to identify and develop Generative and Agentic AI solutions that drive business value Design and implement customized ML models and execute experiments to evaluate the performance of algorithms and identify areas for improvement Finetune and optimize pre-trained large-scale ML models, and deploy them into production environments ensuring scalability and reliability Integrate AI/ML models into agentic AI systems to enhance creativity, productivity, and personalization Create new capabilities that solve critical business problems and influences business leaders to shape product and technology strategy What You Bring MS or Ph.D. in Computer Science, Electrical Engineering, or related field with a focus on Machine Learning. 4+ years of experience in an ML role with an emphasis on data and experiment driven model development Strong research experience in machine learning, computer vision, and/or natural language processing Practical experience training or fine-tuning large-scale ML or LLM models is highly desirable Experience with ML frameworks such as PyTorch and TensorFlow Experience building and productionizing innovative end-to-end Machine Learning systems Proficiency in one or more coding languages such as Python Publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR) are a plus You're inclusive, adapting your style to the situation and diverse global norms of our people. An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding. You're collaborative, building relationships, humbly offering support and openly welcoming approaches. Innovative and creative, you proactively explore new ideas and adapt quickly to change. #LI-VL1 What We OfferThe pay range below is for all roles at this level across all US locations and functions. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. We also offer incentive opportunities that reward employees based on individual and company performance. This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan empowers our people to care for their whole selves. An investment in your future is an investment in ours. Give Back With a charitable giving match and frequent opportunities to get involved, we take an active role in supporting the community.Enjoy Time Away You'll start with 4+ weeks of paid time off a year, plus holidays and sick leave, to rest and recharge.Care for Family Whatever family means to you, we want to support you along the way—including a stipend for fertility care or adoption, medical travel support, and virtual vet care for your fur babies.Prioritize Emotional Wellness With on-demand apps and free confidential therapy sessions, you'll have support no matter where you are.Stay Fit Eating well and being active are important parts of a healthy life. Our onsite Café and gym, plus virtual classes, make it easier.Embrace Flexibility Benefits are best when you have the space to use them. That's why we facilitate a flexible environment so you can find the right balance for you.Base Pay Range$141,000—$219,000 USDEqual Opportunity Employment Policy Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations. Recruiting Agency Policy We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings. Applicant AI Use Policy At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we prohibit the use of generative AI tools to misrepresent a candidate's true skills and qualifications. Permitted uses are limited to basic preparation, grammar, and research, but all submitted content and interview responses must reflect the candidate's genuine abilities and experience. Violation of this policy may result in immediate disqualification from the hiring process. Applicant Privacy Policyhttps://semiconductor.samsung.com/about-us/careers/us/privacy/

🏢 Summary: Senior Research Engineer role focused on designing, evaluating, and deploying production-grade machine learning models for search, ranking, and ads at scale. The position combines applied ML research with end-to-end ownership of solutions, from data exploration to production deployment. It involves translating state-of-the-art research into business impact while mentoring others and collaborating on large-scale systems. 🗂️ Requirements: Master’s or PhD in Machine Learning, Computer Science, Mathematics, Statistics or related STEM field, Strong knowledge of deep learning techniques, Experience in at least one domain: Information Retrieval or Natural Language Processing, Ability to conduct scientific research and iterative experimentation, Experience working with complex, real-world datasets, Proficiency in Python for ML development, Experience with ML frameworks such as PyTorch or TensorFlow 📃 Skills: Python, PyTorch, TensorFlow, Transformers, Pandas, NumPy, DeepLearning, NeuralNetworks, ContrastiveLearning, SemiSupervisedLearning, InformationRetrieval, NLP, Kubernetes, Docker, GitHub, GitHubActions, GCP, AWS, Azure, LLMs 🏢 Description: In the Learning to Rank team we develop machine learning models for search, ranking and ads. Our models serve millions of searches a day. We develop and apply state-of-the-art machine learning methods, helping Allegro grow and innovate with artificial intelligence. Beyond bringing AI to production, we are committed to advance the understanding of machine learning through open collaboration with the scientific community. About the role: As a Senior Research Engineer, you will work at the intersection of cutting-edge machine learning research and real-world products used at scale. You’ll take ownership of ML solutions end to end - from exploring complex data and selecting the right methods, to rigorous evaluation and production deployment. This role is for someone who enjoys navigating uncertainty, keeping pace with a fast-moving ML landscape, and turning research insights into tangible business impact, while also shaping ML expertise within the team and beyond. In your daily work you will handle the following tasks End-to-end ML ownership: Design and deliver production-ready machine learning solutions for Allegro products Data exploration: Analyze and understand complex data sets, identifying relevant data sources for ML use cases Model development & evaluation: Train, evaluate, and experiment with applied ML models using reliable evaluation methods Applied ML research: Translate state-of-the-art ML research into practical improvements for real-world solutions Tooling & methodology: Select ML tools and techniques that best fit concrete business needs Production collaboration: Work closely with cross-functional teams to deploy ML solutions into production Knowledge sharing: Spread ML expertise through internal sessions, presentations, and research activities Mentorship & expertise: Support junior team members and act as a trusted ML expert within the organization We are looking for people who Have a master's or PhD in machine learning, mathematics, computer science, statistics or other STEM fields Have a good knowledge of deep learning techniques (neural networks, contrastive learning, semi-supervised learning) in at least one domain (information retrieval, natural language generation or understanding, etc.) Know the methodology of conducting scientific research and the use of iterative processes of conducting experiments Have experience in working with real data that deviate from the standard, well-developed collections used in research Know Python and libraries necessary to work with model development (PyTorch, Tensorflow, Transformers, Pandas, Numpy, etc.) Nice-to-have: Understanding of Information Retrieval (IR) area Published research papers in ML-related topics Experience in business cooperation, deployments of ML-based solutions in commercial environments Prior experience in running large-scale computation on cloud platform (GCP, AWS or Azure) Prior experience in using LLMs for synthetic data generation/solving business problems What's in it for you Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work. Long term discretionary incentive plan based on Allegro.eu shares (restricted stock units). Annual bonus based on your annual performance and company results. Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms). A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories. A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers). English classes that we pay for related to the specific nature of your job. A training budget, inter-team tourism ( see more here ), hackathons, and an internal learning platform where you will find multiple trainings. An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal. Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy. And that's just the beginning! You can read more about the benefits here . #goodtobehere means that: You will join a team you can count on - we work with top-class specialists who have knowledge- and experience-sharing in their DNA. You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create. You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job. You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support). You will create solutions that will be used (and loved!) by your friends, family and millions of our customers. You will meet the Allegro Scale , which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning. You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (it's been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about! Send us your CV and… see you at Allegro!

🏢 Summary: Senior Research Engineer role focused on designing, developing, and deploying production-ready machine learning models for search, ranking, and ads at scale. The position involves end-to-end ML ownership, from data exploration and experimentation to evaluation and production deployment, while translating state-of-the-art research into business impact. The role combines applied ML research with large-scale production collaboration. 🗂️ Requirements: Master’s or PhD in Machine Learning, Mathematics, Computer Science, Statistics, or related STEM field, Strong knowledge of deep learning techniques, Experience in at least one domain: Information Retrieval or Natural Language Processing, Ability to design and conduct scientific experiments using iterative methodologies, Experience working with complex, real-world datasets, Proficiency in Python, Experience with ML model development libraries (PyTorch or TensorFlow) 📃 Skills: Python, PyTorch, TensorFlow, Transformers, Pandas, NumPy, DeepLearning, NeuralNetworks, ContrastiveLearning, SemiSupervisedLearning, InformationRetrieval, NLP, LLMs, GCP, AWS, Azure, Kubernetes, Docker, Consul, GitHub, GitHubActions 🏢 Description: In the Learning to Rank team we develop machine learning models for search, ranking and ads. Our models serve millions of searches a day. We develop and apply state-of-the-art machine learning methods, helping Allegro grow and innovate with artificial intelligence. Beyond bringing AI to production, we are committed to advance the understanding of machine learning through open collaboration with the scientific community. About the role: As a Senior Research Engineer, you will work at the intersection of cutting-edge machine learning research and real-world products used at scale. You’ll take ownership of ML solutions end to end - from exploring complex data and selecting the right methods, to rigorous evaluation and production deployment. This role is for someone who enjoys navigating uncertainty, keeping pace with a fast-moving ML landscape, and turning research insights into tangible business impact, while also shaping ML expertise within the team and beyond. In your daily work you will handle the following tasks End-to-end ML ownership: Design and deliver production-ready machine learning solutions for Allegro products Data exploration: Analyze and understand complex data sets, identifying relevant data sources for ML use cases Model development & evaluation: Train, evaluate, and experiment with applied ML models using reliable evaluation methods Applied ML research: Translate state-of-the-art ML research into practical improvements for real-world solutions Tooling & methodology: Select ML tools and techniques that best fit concrete business needs Production collaboration: Work closely with cross-functional teams to deploy ML solutions into production Knowledge sharing: Spread ML expertise through internal sessions, presentations, and research activities Mentorship & expertise: Support junior team members and act as a trusted ML expert within the organization We are looking for people who Have a master's or PhD in machine learning, mathematics, computer science, statistics or other STEM fields Have a good knowledge of deep learning techniques (neural networks, contrastive learning, semi-supervised learning) in at least one domain (information retrieval, natural language generation or understanding, etc.) Know the methodology of conducting scientific research and the use of iterative processes of conducting experiments Have experience in working with real data that deviate from the standard, well-developed collections used in research Know Python and libraries necessary to work with model development (PyTorch, Tensorflow, Transformers, Pandas, Numpy, etc.) Nice-to-have: Understanding of Information Retrieval (IR) area Published research papers in ML-related topics Experience in business cooperation, deployments of ML-based solutions in commercial environments Prior experience in running large-scale computation on cloud platform (GCP, AWS or Azure) Prior experience in using LLMs for synthetic data generation/solving business problems What's in it for you Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work. Long term discretionary incentive plan based on Allegro.eu shares (restricted stock units). Annual bonus based on your annual performance and company results. Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms). A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories. A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers). English classes that we pay for related to the specific nature of your job. A training budget, inter-team tourism ( see more here ), hackathons, and an internal learning platform where you will find multiple trainings. An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal. Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy. And that's just the beginning! You can read more about the benefits here . #goodtobehere means that: You will join a team you can count on - we work with top-class specialists who have knowledge- and experience-sharing in their DNA. You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create. You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job. You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support). You will create solutions that will be used (and loved!) by your friends, family and millions of our customers. You will meet the Allegro Scale , which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K+ rps, a Service Mesh with 1M+ rps, tens of petabytes of data, and production-used machine learning. You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (it's been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about! Send us your CV and… see you at Allegro!

🏢 Summary: Senior Machine Learning Engineer role focused on developing and deploying deep learning solutions for prediction, planning, and control within an autonomous driving platform. The position involves leading experiments, building large-scale production ML systems, and collaborating with cross-functional teams to deliver industrial-grade models. It requires extensive experience in autonomous vehicles or robotics and deep expertise in modern ML frameworks and large language models. 🗂️ Requirements: BS/MS/PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Applied Math or related field, 15+ years of experience building ML systems for autonomous vehicles or robotics, Deep understanding of large language models and transformers, Hands-on experience building and deploying large-scale production ML systems, Experience with DNN training, inference and optimization, Strong mathematical foundation in machine learning and deep learning, Proven leadership and innovation track record 📃 Skills: Python, MachineLearning, DeepLearning, LLM, Transformers, PyTorch, TensorFlow, TensorRT, DNN, Robotics, AutonomousVehicles 🏢 Description: What you'll be doing: Researching, implementing, and evaluating deep-learning-based methods for prediction and planning for Autonomous Vehicle products. Leading, designing, running, and analyzing experiments and testing to evaluate the efficiency of solutions on real-world data. Partnering with system software engineering specialists to ship industrial strength ML models. Communicating and collaborating with multi-functional teams. What We're Looking For: BS/MS/PhD in computer science, electrical engineering, mechanical engineering, applied math, or related fields (or equivalent experience) 15+ years of proven experience building ML systems for autonomous vehicles or similar robotics applications Deep understanding of large language models (LLM) and transformers Hands-on experience building large scale production ML systems and deploying them at scale Excellent leadership and track record for innovation to help build the next generation of ML-based planning solutions Experience with deep neural network (DNN) training, inference and optimization in leading frameworks (Pytorch, Tensorflow, TensorRT, etc.) Excellent understanding of the mathematical foundations of machine learning and deep learning Bonus Points: Prior experience as a ML planning lead Proven publication record in ML for planning, vision, or related fields Prior experience building and deploying vision language action or chain of thought models Benefits: Salary range: $271,000—$373,000 USD (base salary) Eligibility to participate in benefits program including medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more.