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1 день назад

Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML (Autonomous Driving)

213 000 - 263 000$
Формат работы
onsite/hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Senior Machine Learning Engineer, Vehicle Interaction & Behavior Policy ML (Autonomous Driving): Developing and releasing learned driving policies for complex navigation and yielding scenarios with an accent on multimodal perception, behavioral planning, and production-ready autonomous driving models. Focus on evaluating policies in closed-loop simulation, meeting strict safety metrics, and transitioning rule-based heuristics to scalable data-driven systems.

Location: Mountain View, California, United States; onsite and hybrid work arrangements are stated.

Salary: $213,000–$263,000 USD annual base salary, plus eligibility for an annual bonus, equity incentives, and company benefits.

Company

Waymo develops autonomous driving technology and operates a fully autonomous ride-hail service powered by the Waymo Driver.

What you will do

  • Develop, evaluate, and release learned driving policies for complex navigation and yielding scenarios.
  • Bridge multimodal perception and planning systems to produce robust behavioral actions.
  • Deploy learned models into closed-loop simulation environments and benchmark them against strict safety metrics.
  • Transition validated models into production releases for real-world autonomous navigation.
  • Advance the replacement of rule-based heuristics with scalable, data-driven learned policies.

Requirements

  • 2–5+ years of experience training and releasing machine learning models in autonomous driving, robotics, or complex spatial AI.
  • Hands-on experience across perception and planning stacks.
  • Experience with learned driving policies, including reinforcement learning or imitation learning.
  • Proficiency with PyTorch or JAX and closed-loop simulator evaluation.
  • Track record of releasing machine learning models to production.

Nice to have

  • Familiarity with Vision-Language-Action models and World Models.
  • Experience using foundation models and AI tools for scenario generation, evaluation analysis, and rapid experimentation.

Culture & Benefits

  • Cross-functional work at the intersection of perception and planning.
  • Participation in a discretionary annual bonus program, subject to eligibility.
  • Equity incentive plan, subject to eligibility.
  • Company benefits program, subject to eligibility.

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