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Описание вакансии
Текст:
TL;DR
ML Engineer, Foundation Model Infrastructure (AI/Autonomous Driving): Building and operating petabyte-scale data systems, ML pipelines, and foundation model infrastructure for the Waymo Driver with an accent on large-scale compute, model evaluation, and safe deployment. Focus on developing distributed ML systems, automating benchmarking and monitoring, and improving the reliability and efficiency of the end-to-end machine learning lifecycle.
Location: On-site or hybrid in Mountain View, California; San Francisco, California; New York City, New York; or Kirkland, Washington
Salary: $175,000–$215,000 USD per year, plus potential annual bonus, equity, and benefits.
Company
Waymo develops autonomous driving technology and operates a fully autonomous ride-hail service powered by the Waymo Driver.
What you will do
- Build and operate petabyte-scale data systems and machine learning pipelines for foundation model development.
- Move foundation models from research prototypes into robust components of the Waymo Driver.
- Create automated infrastructure for model benchmarking, continuous monitoring, and safe releases.
- Use large-scale compute and frameworks such as Flume and JAX to process massive datasets and train and deploy complex models.
- Improve the speed, reliability, and efficiency of the end-to-end ML development lifecycle.
- Collaborate with AI Foundations, ML, and Platform specialists to turn model innovations into on-road improvements.
Requirements
- Master’s degree in Computer Science, Machine Learning, Robotics, or a similar technical field, or equivalent practical experience.
- Proficiency in Python and C++.
- Familiarity with a modern deep learning framework such as PyTorch, JAX, or TensorFlow.
- Experience building or maintaining large-scale data pipelines or ML infrastructure, such as Flume, Spark, Borg, or Kubeflow.
- Experience with large codebases, distributed systems, MLOps platforms, or ML model evaluation is valuable.
Nice to have
- Experience in autonomous vehicle planning and related research.
- Experience with model versioning, experiment tracking, or CI/CD for machine learning.
- Industrial or research experience developing methodologies for evaluating ML models.
Culture & Benefits
- Work with the AI Foundations team on reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
- Health, dental, vision, life, and disability insurance.
- 401(k) with company match, paid vacation, sick time, paid holidays, and parental leave.
- Eligibility for an annual bonus program, equity incentive plan, and company benefits.
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