Staff Machine Learning Engineer
Motional
Job Description
Mission Summary At Motional, weâre 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 MLâpowered multimodal data mining framework, is the engine that powers this discovery.
What Youâll Do Define Technical Strategy & Roadmaps Develop and execute multiâquarter, highâimpact technical roadmaps for core ML systems. Proactively inform leadership to guide reprioritization, ensuring initiatives consistently drive teamâwide and departmentâlevel OKRs and KPIs. Architect SystemâLevel Solutions Own the systemâlevel architecture for complex ML products.
Design scalable frameworks for massive data mining and highly optimized, realâtime inference across GPU/CPU clusters. Drive CrossâFunctional Execution Lead multiâperson projects to completion across teams. Influence partner teamsâ technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment.
Elevate Engineering Excellence Establish departmentâwide standards for ML system design, code quality, testing, and deployment. Deliver processes to proactively address issues and participate in orgâwide incident response planning. Operate as a Generalist Expert Apply a broad toolkit of ML techniques (deep learning, representation learning, active learning, generative AI) to solve complex, ambiguous problems.
Unblock yourself and your team when facing unprecedented technical challenges. Mentor and Lead Act as a role model and technical goâto person. Coach senior and junior engineers, lead architectural reviews, and elevate Motionalâs engineering culture through internal documentation, tech talks, and collaborative design.
What Weâre Looking For (MustâHaves) BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience) 8 years of handsâon ML engineering experience with a proven track record of owning architecture, deployment, and optimization of largeâscale ML systems Demonstrated experience working with multimodal foundation models in ML production systems including integration, scaling, fineâtuning, or deployment of models that process multiple data modalities (e.g., camera, LiDAR, radar, text) Demonstrated technical leadership defining multiâquarter roadmaps, leading multiâperson initiatives, and driving departmentâlevel technical strategy Expertâlevel proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX) backed by strong software engineering fundamentals (system design, CI/CD, containerization) Broad ML generalist knowledge with practical experience spanning model training, deep learning architectures, evaluation methodologies, and production deployment at scale Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for latency, throughput, and hardware efficiency Proven ability to mentor peers, explain complex tradeâoffs to leadership, and drive consensus across disparate teams Bonus Points (NiceâtoâHaves) MS/PhD in Computer Science, Machine Learning, or a related field Background in autonomous driving, robotics, or complex realâtime decisionâmaking systems Experience with massiveâscale ML data mining, active learning loops, and contrastive/representation learning Familiarity with multimodal learning, sensor fusion, or large foundation models Deep knowledge of model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms Demonstrated experience leading orgâwide severity reviews or establishing incident response planning for missionâcritical ML platforms Salary Range $205,000 - $272,500 USD Benefits Medical, dental, vision 401k with a company match Health saving accounts Life insurance, pet insurance, and more 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 EâVerify.
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