Machine Learning Engineer, Growth

🏢 Summary: Staff Software Engineer role leading the technical strategy and architecture of a scalable Incentive Offers platform, building identity, decisioning, and measurement systems for real-time, high-volume distributed environments. The position focuses on architecting data-intensive, event-driven services that connect physical-world signals with digital member profiles and automated campaigns. You will drive platform evolution, solve complex distributed systems challenges, and shape engineering standards across the organization. 🗂️ Requirements: Advanced degree in Computer Science or related field, 8+ years building customer-facing applications and distributed systems, Expert proficiency in Scala, Java, or JVM-based languages, Experience architecting data-intensive and real-time event-driven systems, Experience leading technical strategy for large engineering initiatives, Experience with AI/ML tools in engineering or system intelligence, Strong experience with high-volume transaction processing and data consistency, Experience designing observability, monitoring, and automated testing solutions 📃 Skills: Scala, Java, TypeScript, React, JVM, MySQL, PostgreSQL, Snowflake, AWS, Git, GitHub, Datadog, AI, ML 🏢 Description: Who we are The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it. Who you are Metropolis is seeking a Staff Software Engineer to lead the technical evolution of our Incentive Offers platform, serving as a critical architect for our identity, decisioning, and measurement infrastructure. You will play a pivotal role in transforming vision-based location signals into a scalable demand engine for our partners by building the platform layer that connects arrivals to automated campaigns. As a technical steward and influencer, you will solve complex technical challenges that few others can while mentoring engineers and setting the direction for project impact and engineering craft across the organization. What you'll do Define the technical strategy and long-term roadmap for the Incentive Offers platform Architect scalable services for offer management, campaign eligibility, and business rule enforcement Design high-throughput infrastructure for real-time member communication and preference management Develop identity resolution systems that connect physical-world vehicle signals with digital member profiles Build robust attribution and measurement engines to track closed-loop redemption across diverse verticals Engineer seamless integrations between our platform and external partner systems or point-of-sale technologies Mentor senior engineering talent and advocate for high standards of engineering craft and efficiency Solve complex distributed systems problems related to high-volume transaction processing and data consistency Partner with Product and Marketing leaders to translate business objectives into scalable technical solutions Identify and resolve systemic bottlenecks to improve developer velocity and system reliability What we're looking for Advanced degree in Computer Science or a related technical field 8+ years of experience building customer-facing applications and complex distributed systems Demonstrate expert proficiency in Scala, Java, or similar JVM-based languages Experience with AI/ML tools to improve engineering productivity or system intelligence Show a proven track record of leading technical strategy for significant engineering initiatives Possess a strong background in architecting data-intensive platforms and real-time event-driven systems Communicate complex technical concepts effectively to both technical and non-technical stakeholders Mentor engineers to foster a high-performance engineering culture and technical growth Design for operational excellence including observability, monitoring, and automated testing Navigate high levels of ambiguity and deliver results in a fast-paced environment While not required, these are a plus: Familiarity with marketing technology stacks or consumer-facing loyalty platforms Experience working in high-growth startup environments or industry-leading tech companies Our Stack Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited) Datastores: MySQL, PostgreSQL, Snowflake Cloud: AWS Version control: Git & GitHub AI Tooling: Copilot on GitHub and Claude Code Observability: Datadog 4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $200,000.00 USD to $250,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-OnsiteMetropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting. As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records. Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.

🏢 Summary: Machine Learning Engineer role focused on designing, building, and deploying production ML systems across Lyft Business, including pricing, fraud detection, marketplace optimization, and agentic AI applications. The position involves owning models end-to-end, developing scalable ML infrastructure, and translating business problems into impactful ML solutions. The role operates in high-scale environments influencing revenue, operations, and user experience. 🗂️ Requirements: Experience with GenAI and LLM ecosystems, Experience building and deploying production ML models, Experience with pricing, marketplace, or fraud ML problems, Experience with feature engineering and ML pipelines, Experience with cloud ML services, Ability to productionize research prototypes, Experience running experiments and evaluating ML performance, Ability to design scalable ML systems, Proficiency in writing production-quality code 📃 Skills: Python, MachineLearning, LLM, GenAI, RAG, LangChain, LangGraph, SageMaker, Bedrock, AWS, GraphNN, KnowledgeGraphs, NetworkAnalysis, APIs, Experimentation 🏢 Description: At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business. Responsibilities: Develop and deploy ML models across multiple problem domains — including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection — in production environments serving millions of rides Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Partner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement Identify new opportunities where ML can create leverage across Lyft Business verticals (Healthcare, Lyft Pass, Business Travel) and pitch solutions Contribute to team engineering standards — code quality, observability, documentation, and testing practices Experience: Experience with GenAI / LLM ecosystems — prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning Exposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis) Experience with pricing, marketplace, or fraud-related ML problems Familiarity with cloud ML services (AWS SageMaker, Bedrock) or internal ML platforms Track record of identifying and scoping ML projects independently, not just executing on pre-defined specs Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible Subsidized commuter benefits Monthly Lyft credits and complimentary Lyft Pink membership Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the San Francisco area is $176,000-$211,200, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

🏢 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.