6 дней назад
Research Scientist, RL for Autonomous Planning & World Modeling (AI)
204 000 - 259 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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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