Motional

Motional

Motional is a leading company in driverless technology and autonomous vehicles, leveraging decades of industry expertise to develop and deploy safe and reliable autonomous vehicles. With a powerful DNA combining Aptiv's automotive technology and Hyunda...

Automotive
1K-5K
Founded 2020
$20M raised

Description

  • Define and execute multi-quarter technical roadmaps for core machine learning systems.
  • Own system-level architecture for large ML products and scalable data-mining frameworks.
  • Design highly optimized, real-time inference across GPU and CPU clusters.
  • Lead multi-person, cross-functional projects and align partner teams on shared technical problems.
  • Establish department-wide standards for ML system design, code quality, testing, and deployment.
  • Develop processes to proactively address issues and support org-wide incident response planning.
  • Apply broad ML techniques such as deep learning, representation learning, active learning, and generative AI to ambiguous problems.
  • Mentor senior and junior engineers, lead architectural reviews, and serve as a technical go-to person.
  • Create internal documentation and tech talks to strengthen engineering culture and knowledge sharing.

Requirements

  • BS in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
  • 8+ years of hands-on ML engineering experience.
  • Proven experience owning architecture, deployment, and optimization of large-scale ML systems.
  • Experience working with multimodal foundation models in production systems, including integration, scaling, fine-tuning, or deployment.
  • Demonstrated technical leadership in defining multi-quarter roadmaps and driving department-level technical strategy.
  • Expert-level proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong software engineering fundamentals, including system design, CI/CD, and containerization.
  • Broad ML generalist experience spanning model training, deep learning architectures, evaluation, and production deployment at scale.
  • Experience deploying ML models in cloud environments such as AWS, GCP, or Azure and optimizing for latency, throughput, and hardware efficiency.
  • Proven ability to mentor peers, explain trade-offs to leadership, and drive consensus across teams.
  • MS or PhD in Computer Science, Machine Learning, or a related field is preferred.
  • Background in autonomous driving, robotics, or complex real-time decision-making systems is preferred.
  • Experience with massive-scale ML data mining, active learning loops, and contrastive or representation learning is preferred.
  • Familiarity with multimodal learning, sensor fusion, or large foundation models is preferred.
  • Deep knowledge of model serving tools such as TF Serving, Triton, or TorchServe, and enterprise MLOps platforms is preferred.
  • Experience leading org-wide severity reviews or establishing incident response planning for mission-critical ML platforms is preferred.

Benefits

  • Hybrid schedule with in-office time in Boston, Pittsburgh, or Las Vegas, or fully remote work.
  • Base salary range of $205,000 to $272,500 USD.
  • Eligibility for additional compensation such as bonus or company equity.
  • Medical, dental, and vision insurance.
  • 401(k) with company match.
  • Health savings accounts.
  • Life insurance.
  • Pet insurance.

Interested in this position?

Apply directly on the company website

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