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 the system-level architecture for large-scale ML products and platforms.
  • Design scalable frameworks for massive data mining and highly optimized real-time inference across GPU/CPU clusters.
  • Lead multi-person projects across teams and drive them to completion.
  • Influence partner teams’ roadmaps to solve shared problems and build alignment.
  • Establish department-wide standards for ML system design, code quality, testing, and deployment.
  • Develop processes to proactively address issues and participate in incident response planning.
  • Apply a broad range of ML techniques to solve ambiguous technical problems.
  • Mentor senior and junior engineers and lead architectural reviews.
  • Create internal documentation, tech talks, and collaborative design processes to strengthen engineering culture.

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 ML production systems.
  • Experience integrating, scaling, fine-tuning, or deploying models that process multiple modalities such as camera, LiDAR, radar, or text.
  • Demonstrated technical leadership in defining roadmaps, leading initiatives, and shaping department-level strategy.
  • Expert-level proficiency in Python.
  • Experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong software engineering fundamentals, including system design, CI/CD, and containerization.
  • Broad ML 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.
  • Ability to optimize for latency, throughput, and hardware efficiency.
  • 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 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 is preferred.
  • Experience leading org-wide severity reviews or incident response planning for mission-critical ML platforms is preferred.

Benefits

  • Base salary range of $205,000 to $272,500 USD.
  • Additional compensation may include a bonus and company equity.
  • Hybrid schedule with in-office collaboration in Boston, Pittsburgh, or Las Vegas, or the option to work fully remote.
  • Medical, dental, and vision coverage.
  • 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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