Machine Learning Engineer

🏢 Summary: The role focuses on designing, building, and operating production-grade machine learning solutions using classical ML and deep learning models. You will develop end-to-end ML pipelines, ensure robustness and reproducibility in production, and collaborate on technical solution design. The position emphasizes strong Python engineering and experience with cloud-based ML platforms. 🗂️ Requirements: Degree in ComputerScience, DataScience, Mathematics or related field, Experience building production-grade machine learning pipelines, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI and CD pipelines, Experience with cloud-based ML platforms, Ability to design, train and optimize ML and deep learning models, Experience ensuring robustness and reproducibility in production environments 📃 Skills: Python, MachineLearning, DeepLearning, Pipelines, FeatureEngineering, Deployment, Monitoring, Git, CI, CD, Databricks, AWS, Azure, GCP, Cloud, VersionControl 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution. Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of machine learning solutions in production environments Implement structured and versioned ML workflows supporting reliable model development and operation Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Solid experience building and operating production-grade machine learning pipelines Strong Python engineering skills , including clean code practices and software engineering best standards Hands-on experience with Git-based version control and working with CI/CD pipelines as a user Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: Machine Learning Engineer role focused on designing, deploying, and operating enterprise-grade classical ML and Generative AI solutions. The position involves building end-to-end ML pipelines, integrating LLM-based applications, and ensuring production stability in cloud-based environments. The role includes hybrid work, ongoing training opportunities, and a flexible benefits platform. 🗂️ Requirements: Degree in Computer Science, Data Science, Mathematics or related field, Experience delivering Generative AI solutions, Knowledge of LLM architectures and limitations, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms, Experience with cloud environments, Fluent English, Fluent Polish, Availability for hybrid work with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, LLM, GenAI, MachineLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The offer is for a Machine Learning Engineer responsible for designing, implementing, and operating enterprise-grade Machine Learning and Generative AI solutions. The role focuses on building end-to-end ML and GenAI pipelines, integrating LLM-based solutions, and ensuring production robustness and performance. You will concentrate on technical delivery and system integration within cloud-based environments. 🗂️ Requirements: University degree in Computer Science, Data Science, Mathematics or related field, Practical experience delivering Generative AI solutions, Strong understanding of LLM architectures and limitations, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI/CD pipelines, Hands-on experience with ML and GenAI platforms, Experience with cloud environments (AWS, Azure, GCP or Databricks), Experience building and operating production-grade ML systems 📃 Skills: Python, MachineLearning, GenerativeAI, LLM, Git, CICD, Databricks, AWS, Azure, GCP, APIs, MLOps 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: Machine Learning Engineer role focused on designing, deploying, and operating enterprise-grade classical ML and Generative AI solutions in hybrid cloud environments. The position involves building end-to-end ML pipelines, integrating LLM-based systems, and ensuring production stability and scalability. Candidates work closely with ML and data teams while concentrating on technical implementation and operational excellence. 🗂️ Requirements: Degree in Computer Science, Data Science, Mathematics or related field, Experience delivering Generative AI solutions, Understanding of LLM architectures and limitations, Strong Python engineering skills, Knowledge of clean code and software engineering best practices, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms, Experience with cloud environments, Fluent English, Fluent Polish, Availability for hybrid work with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, LLM, GenAI, MachineLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The role focuses on designing, implementing, and operating enterprise-grade Machine Learning and Generative AI solutions, with responsibility for end-to-end pipelines and production stability. The engineer works hands-on with classical ML and LLM-based systems, ensuring robust integration into existing enterprise environments. The position emphasizes technical ownership of ML & GenAI use cases in close collaboration with internal teams. 🗂️ Requirements: University degree in Computer Science, Data Science, Mathematics or related field, Practical experience delivering Generative AI solutions, Strong understanding of LLM architectures and limitations, Strong Python engineering skills with clean code practices, Hands-on experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms in cloud environments (Databricks, AWS, Azure or GCP), Fluent English and Polish, Availability for hybrid work (1–2 office visits per week) 📃 Skills: Python, MachineLearning, GenerativeAI, LLM, Git, CICD, Databricks, AWS, Azure, GCP, APIs 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: Distinguished Machine Learning Engineer role within the Autonomy Behaviors team focused on developing and deploying deep learning solutions for prediction, planning, and control in autonomous vehicles. The position involves leading large-scale ML experimentation, building production-grade models, and collaborating cross-functionally to deliver industrial-strength systems. Candidates must bring extensive experience in autonomous vehicle ML systems, deep neural networks, and large-scale model deployment. 🗂️ 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 similar robotics applications, Deep understanding of large language models (LLM) and transformers, Hands-on experience building and deploying large-scale production ML systems, Experience training, optimizing, and deploying deep neural networks in PyTorch, TensorFlow, or TensorRT, Strong mathematical foundation in machine learning and deep learning, Proven leadership and innovation in ML-based planning solutions 📃 Skills: Python, MachineLearning, DeepLearning, LLM, Transformers, DNN, PyTorch, TensorFlow, TensorRT, Prediction, Planning, Control, Optimization 🏢 Description: Motional is seeking a distinguished Machine Learning Engineer to join its Autonomy team in Behaviors. As a member of our team you will develop key features for our autonomous driving platform. In this role, you will apply machine learning to a mix of prediction, planning, and control problems. The candidate is required to have hands-on experience and deep knowledge in machine learning. Understanding of deep neural networks, autonomous vehicles, and domain adaptation is highly desirable. You should have strong research, SW development, communication, interpersonal, and analytical skills. 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 Salary Range $271,000—$373,000 USD 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 reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. Benefits: Candidates for certain positions are eligible to participate in the benefits program, including but not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

🏢 Summary: Senior Machine Learning Engineer role focused on building and scaling end-to-end recommendation systems for personalized content and workout experiences. The position involves developing real-time ML services, running experiments, and deploying production-grade models in a cloud-based environment. You will contribute to unified recommendation architecture and LLM-driven personalization initiatives. 🗂️ Requirements: 4+ years of experience in machine learning, Experience in recommender systems or applied ML domains, Degree in Computer Science, Machine Learning, Statistics, Mathematics or related quantitative field, Hands-on experience building, training and evaluating ML models, Strong software engineering skills, Professional experience with Python, Experience with large-scale data pipelines, Experience with distributed data processing, Experience with Spark and Airflow, Experience with AWS or similar cloud environment, Experience with Kubernetes and production serving technologies, Experience with A/B testing and experiment analysis 📃 Skills: Python, Spark, Airflow, AWS, S3, Kubernetes, RecommenderSystems, DeepLearning, Transformers, LLMs, MLOps, REST, gRPC, FastAPI, ABTesting 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Machine Learning Engineer to join the Personalization team, which owns the recommendation systems powering content discovery across the ecosystem. In this role, you will work on end-to-end ML systems: building and training models, improving real-time recommendation services, running experiments, and deploying scalable solutions into production. You will help evolve the recommendation platform from multiple models toward a more unified, real-time architecture, while also contributing to company's IQ initiatives involving LLMs, personalized plans, and AI-powered member experiences. Key takeaways: Stack : Python, Spark, Airflow, AWS, S3, Kubernetes, recommender systems, Deep Learning, Transformers, LLMs, MLOps, REST/gRPC/FastAPI, A/B testing Salary : 31 000 PLN - 35 000 PLN gross on the Contract of Employment Working model : Hybrid - 3 days/week from the office Location : ul. Grzybowska 60, Warsaw Recruitment process : A call with MOTIFE Recruiter Hiring Manager screening Coding interview Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting) Responsibilities: Build, train, evaluate, and improve ML models powering personalized workout and content recommendations. Develop and maintain data and ML pipelines using Python, Spark, Airflow, AWS, and S3. Productionize, deploy, monitor, and optimize ML models and recommendation services. Improve real-time model serving, including latency, scalability, reliability, and infrastructure costs. Support the evolution of recommendation systems toward unified rankers, candidate generation, and inference services. Run A/B tests and analyze experiment results with Product Analysts to measure product and member impact. Contribute to IQ initiatives, including personalized plans, insights, LLM-based features, and responsible AI practices. Collaborate with ML Engineers, Data Engineers, Software Engineers, Platform Engineers, Product Managers, and Analysts to deliver scalable personalization features. Requirements: 4+ years of experience in machine learning, ideally in recommender systems, NLP, computer vision, or another applied ML domain. Degree in Computer Science, Machine Learning, Statistics, Mathematics, Operational Research, or another quantitative field. Strong hands-on experience building, training, evaluating, and improving ML models. Solid software engineering skills, including clean code, data structures, algorithms, and production readiness. Professional experience with Python; experience with Java, Kotlin, Go, C, or C++ is a plus. Experience with large-scale data pipelines, distributed processing, and orchestration tools such as Spark and Airflow. Familiarity with cloud-based ML environments, preferably AWS, and production serving technologies such as Kubernetes, REST, gRPC, or FastAPI. Strong communication skills and the ability to work cross-functionally with product, analytics, platform, data, and engineering teams. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If this sounds like your next step, we’d love to hear from you! Please apply via our careers page and submit your CV in English.

🏢 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.

🏢 Summary: Machine Learning Engineer role focused on building and scaling entity resolution and knowledge graph models to uncover hidden connections within China’s economic landscape. The position involves developing, fine-tuning, and deploying ML models operating on tens of millions of records, as well as enhancing agentic workflows and large-scale data pipelines. You will collaborate cross-functionally to expand AI capabilities and integrate advanced analytics into a high-impact intelligence platform. 🗂️ Requirements: 4+ years of experience with clustering-based ML problems, Experience with knowledge graphs or entity resolution domains, End-to-end ML model development and production deployment experience, Experience with model experimentation, training, testing, tuning, and deployment, Strong Python programming skills, Strong SQL skills 📃 Skills: Python, SQL, Clustering, Classification, Regression, Embeddings, KNN, SVM, NLP, DeepLearning, PySpark, Temporal, FastAPI, Scikit-learn, NumPy, Docker, Terraform, Kubernetes, OCR 🏢 Description: About The Role: As a Machine Learning Engineer, you will work across data systems to uncover the source of truth behind China’s economic landscape. This role focuses on building models that power entity resolution and the knowledge graph, uncovering hidden connections within the Chinese economy. You will contribute to MCP servers and agentic pipelines to classify, cluster, and enrich millions of entities, while collaborating with engineering, product, and research to scale data ingestion and AI capabilities. What You'll Do: - Fine-tune entity resolution algorithms to uncover hidden connections between people and organizations - Expand the knowledge graph with alternative data to map power structures - Train, test, and deploy ML models operating on tens of millions of records daily - Define and implement evaluation harnesses for classical ML and agentic systems - Build agent workflows into internal tools to improve research scale and speed What We’re Looking For: - 4+ years of experience working on clustering-type ML problems (e.g., knowledge graphs, entity resolution, recommendation engines, cohort analysis, anomaly detection) - End-to-end production ML experience, including experimentation, training, testing, tuning, and deployment - Experience with model families such as clustering, classification/regression, dimensionality reduction, embeddings, nearest-neighbor methods (KNN, SVM), ensembles, NLP, and deep learning - Strong experience with Python and SQL Nice to Have: - Experience with frontier/SOTA models or fine-tuning LLMs - Experience working with large, heterogeneous, unstructured datasets - Experience with semantic search, computer vision (OCR), or linear optimization - Experience with PySpark, Temporal, FastAPI, Scikit-learn, NumPy, Docker, Terraform, Kubernetes - Early-stage startup experience - B2B SaaS experience Benefits & Perks: - Competitive compensation including salary and equity - 100% company-paid Medical, Dental, and Vision coverage - FSA, HSA, and 401(k) options - Generous paid time off and company-wide holidays - Pre-tax commuter benefits - Hybrid office schedule - Compensation range: $150K - $195K

🏢 Summary: The offer is for a Machine Learning Systems Engineer focused on optimizing large-scale distributed training systems for frontier models. The role centers on performance profiling, GPU kernel development, and improving throughput, scalability, and reliability of ML training pipelines. It directly supports accelerating model convergence through high-performance systems engineering. 🗂️ Requirements: Bachelor’s, Master’s or PhD in Computer Science, Computer Engineering or related field, Strong proficiency in Python, Extensive hands-on experience with PyTorch, Experience with distributed training using PyTorch Distributed, Experience optimizing ML model training and inference performance, Experience with GPU kernel development in CUDA or Triton, Ability to perform performance profiling and bottleneck analysis, Strong understanding of machine learning concepts and architectures 📃 Skills: Python, PyTorch, CUDA, Triton, Nsight, PyTorchDistributed, GPU, KernelFusion, Sharding, Tiling 🏢 Description: Mission Summary:We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models. What you'll be doing: Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time. Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed. Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads. Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput. What we're looking for: Education: Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline. Software Engineering: Strong proficiency in Python. ML Frameworks: Extensive hands-on experience with PyTorch. ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes. Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges. 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.