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June 24, 2026

Staff Machine Learning Engineer

Senior • Hybrid

San Francisco, CA

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 rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, powers this discovery.

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for machine learning systems that power data discovery and model improvement lifecycles. You will architect scalable systems spanning multimodal representation learning, active learning loops, and high-efficiency production inference. You will own system-level architecture, lead multi-quarter initiatives, and partner across engineering to influence department-wide technical strategy while establishing robust processes and mentoring others.

What You'll Do

  • Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps aligned with team and department OKRs and KPIs.
  • Architect System-Level Solutions: Own architecture for complex ML products and design scalable frameworks for massive data mining and optimized real-time inference across GPU/CPU clusters.
  • Drive Cross-Functional Execution: Lead multi-person projects and influence partner roadmaps to solve shared technical challenges.
  • Elevate Engineering Excellence: Establish standards for ML system design, code quality, testing, deployment, and incident response planning.
  • Operate as a Generalist Expert: Apply deep learning, representation learning, active learning, and generative AI to complex problems.
  • Mentor and Lead: Coach engineers, lead architectural reviews, and contribute to engineering culture.

What We're Looking For (Must-Haves)

  • BS in Computer Science, Machine Learning, or related field (or equivalent practical experience)
  • 8+ years of hands-on ML engineering experience with large-scale ML systems
  • Experience with multimodal foundation models in production systems (camera, LiDAR, radar, text)
  • Demonstrated technical leadership across multi-quarter, multi-person initiatives
  • Expert proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX)
  • Strong software engineering fundamentals including system design, CI/CD, and containerization
  • Broad ML experience across training, architectures, evaluation, and large-scale deployment
  • Experience deploying ML models in cloud environments (AWS, GCP, or Azure)
  • Proven mentorship and cross-team collaboration skills

Bonus Points (Nice-to-Haves)

  • MS or PhD in Computer Science, Machine Learning, or related field
  • Background in autonomous driving, robotics, or real-time decision-making systems
  • Experience with large-scale ML data mining, active learning loops, and contrastive/representation learning
  • Familiarity with multimodal learning, sensor fusion, or large foundation models
  • Experience with model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms
  • Experience leading severity reviews or incident response planning for mission-critical ML platforms

Work Arrangement & Compensation

  • Hybrid schedule (Boston, Pittsburgh, Las Vegas) or fully remote
  • Base salary range: $205,000—$272,500 USD
  • Eligible for additional compensation such as bonus or company equity
  • Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more

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