Machine Learning Engineer

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.

• Define Technical Strategy & Roadmaps
  Develop and execute multi‑quarter, high‑impact technical roadmaps for core ML systems. Proactively inform leadership to guide reprioritization, ensuring initiatives consistently drive team‑wide and department‑level OKRs and KPIs.
• Architect System‑Level Solutions
  Own the system‑level architecture for complex ML products. Design scalable frameworks for massive data mining and highly optimized, real‑time inference across GPU/CPU clusters.
• Drive Cross‑Functional Execution
  Lead multi‑person projects to completion across teams. Influence partner teams’ technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment.
• Elevate Engineering Excellence
  Establish department‑wide standards for ML system design, code quality, testing, and deployment. Deliver processes to proactively address issues and participate in org‑wide 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 go‑to person. Coach senior and junior engineers, lead architectural reviews, and elevate Motional’s engineering culture through internal documentation, tech talks, and collaborative design.

• BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience)
• 8 years of hands‑on ML engineering experience with a proven track record of owning architecture, deployment, and optimization of large‑scale ML systems
• Demonstrated experience working with multimodal foundation models in ML production systems including integration, scaling, fine‑tuning, or deployment of models that process multiple data modalities (e.g., camera, LiDAR, radar, text)
• Demonstrated technical leadership defining multi‑quarter roadmaps, leading multi‑person initiatives, and driving department‑level technical strategy
• Expert‑level proficiency in Python and ML frameworks (PyTorch, Tensor Flow, 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 trade‑offs to leadership, and drive consensus across disparate teams

• MS/PhD in Computer Science, Machine Learning, or a related field
• Background in autonomous driving, robotics, or complex real‑time decision‑making systems
• Experience with massive‑scale 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, Torch Serve) and enterprise MLOps platforms
• Demonstrated experience leading org‑wide severity reviews or establishing incident response planning for mission‑critical ML platforms

Salary Range $205,000 - $272,500 USD

• 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 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.