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Principal AI​/ML Engineer

Job in Sunnyvale, Santa Clara County, California, 94087, USA
Listing for: Jobtailor
Full Time position
Listed on 2026-07-13
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Software Architect, Robotics
Salary/Wage Range or Industry Benchmark: 180000 - 280000 USD Yearly USD 180000.00 280000.00 YEAR
Job Description & How to Apply Below
  • Define and drive the technical vision and architecture for trajectory generation systems used in autonomous driving
  • Lead the development of ML-based trajectory generation models capable of handling complex and dynamic driving environments
  • Architect scalable training pipelines using large-scale driving datasets and simulation environments
  • Guide the integration of trajectory generation models into real-time onboard systems with strict latency and safety requirements
  • Influence the design of next-generation embodied AI architectures for driving
  • Mentor senior engineers and help develop the next generation of technical leaders
  • Raise the bar for engineering excellence, modeling rigor, and production-quality systems
  • Foster a culture of innovation, ownership, and collaborative problem solving
  • Lead complex technical initiatives spanning multiple teams across the autonomous driving stack
  • Collaborate closely with teams working on data, perception, simulation, safety validation, onboard systems
  • Define roadmaps and priorities aligned with product milestones and safety goals
  • Drive solutions from research prototypes through production deployment
Requirements
  • MS or PhD in Computer Science, Robotics, Machine Learning, or related field
  • Experience leading technical teams delivering production ML systems
  • Deep expertise in one or more areas: robotics planning and control, imitation learning or reinforcement learning, generative models, large-scale machine learning systems
  • Strong software engineering skills (Python, C++, or similar)
  • Experience deploying ML models into real-world or safety-critical environments
  • Demonstrated ability to define architecture and drive large technical initiatives across teams
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