Назад
6 дней назад

Research Scientist, RL for Autonomous Planning & World Modeling (AI)

204 000 - 259 000$
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
Research Scientist, RL for Autonomous Planning & World Modeling (AI): Researching and developing reinforcement learning and distillation techniques for autonomous vehicle trajectory planning, with an accent on foundation world models, scalable training, and rigorous evaluation. Focus on post-training world models, integrating emerging research into distributed RL infrastructure, and scaling inference and training across many machines.

Location: On-site in Mountain View, San Francisco, New York City, or Kirkland, United States. The role is described as hybrid, and remote availability depends on the specific location.

Salary: $204,000–$259,000 USD per year, plus eligibility for an annual bonus and equity incentive plan.

Company

Waymo develops autonomous driving technology and the Waymo Driver for fully autonomous ride-hail services and other vehicle platforms.

What you will do

  • Participate in foundation world model post-training and evaluation.
  • Research and develop reinforcement learning and distillation techniques for autonomous vehicle trajectory planning.
  • Integrate emerging AI research into internal reinforcement learning infrastructure.
  • Conduct rigorous ablation studies to identify and scale promising methods.
  • Collaborate with engineering and research teams across Waymo on post-training practices and technical methods.

Requirements

  • PhD or master’s degree in computer science, machine learning, robotics, or a related technical field.
  • 3+ years of industry or postdoctoral research experience in reinforcement learning or foundation models.
  • Original contributions demonstrated through high-impact publications, technical blog posts, or significant open-source work.
  • Proficiency implementing scalable, distributed, and performant model-training flows, including data parallelism and FSDP.
  • Willingness to work with the complexity of globally distributed inference infrastructure.

Nice to have

  • Research focus on reinforcement learning, foundation models, or multimodal learning.
  • Experience designing and deploying reinforcement learning infrastructure for on-policy learning or alignment with human preferences.
  • First-author publications at top-tier venues or significant open-source machine learning projects.
  • Experience with large-scale training infrastructure, model sharding, or tensor-parallel inference.

Culture & Benefits

  • Health, dental, vision, life, and disability insurance for eligible US-based employees.
  • 401(k) retirement benefits with company matching.
  • Paid vacation, sick time, holidays, maternity leave, and baby bonding leave.
  • Collaboration with research teams across Waymo and Alphabet.
  • Access to discretionary bonus and equity incentive programs, subject to eligibility.

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