2 дня назад
Staff Software Engineer, Simulation ML Infrastructure (AI/ML)
251 000 - 310 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Software Engineer, Simulation ML Infrastructure (AI/ML): Building and scaling distributed infrastructure for foundation-model-powered autonomous-driving simulations with an accent on massive model scaling, ML accelerator optimization, and planet-scale data generation. Focus on designing ML lifecycle systems, profiling accelerator performance, and solving complex infrastructure challenges across data engineering, model training, and simulation.
Location: Onsite in Mountain View or San Francisco, California, United States
Salary: $251,000–$310,000 USD gross annual base salary, plus discretionary annual bonus, equity incentives, and company benefits.
Company
Waymo develops autonomous driving technology and operates a fully autonomous ride-hailing service powered by the Waymo Driver.
What you will do
- Build advanced AI/ML infrastructure for realistic, multi-agent autonomous-driving simulations using large foundation models.
- Design and scale distributed systems supporting planet-scale dataset generation, model training, and evaluation across the ML lifecycle.
- Drive architecture and technical decisions for large, complex systems spanning data engineering, model development, and simulation.
- Collaborate with the Realism Modeling teams in London and Oxford to improve simulation fidelity and steerability.
- Translate product and business objectives into measurable technical requirements and aligned system designs.
Requirements
- 6+ years of professional software engineering experience, including at least 4 years building or scaling large-scale ML infrastructure.
- Experience developing, training, deploying, and optimizing machine learning systems from data through production models.
- Strong experience with ML infrastructure tools such as DeepSpeed, PyTorch, TensorFlow, Ray, or similar frameworks.
- Knowledge of modern ML models and algorithms, including autoregressive transformers, and experience profiling ML accelerators to identify bottlenecks.
- Ability to lead ambiguous technical problems end to end, build infrastructure and tooling, and communicate complex concepts clearly.
Nice to have
- Practical familiarity with autonomous driving, simulation, and ML accelerators.
Culture & Benefits
- Work with a research engineering team advancing high-fidelity autonomous-driving simulations.
- Collaborate across international teams in the United States and United Kingdom.
- Eligibility for a discretionary annual bonus and equity incentive plan.
- Generous company benefits program, subject to eligibility requirements.
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