- Location
- Oxford, UK ; London, UK · Oxford (UK-OXF-WOOD46)
- Workplace
- Hybrid
- Department
- Education
- Seniority
- Senior
- Experience
- 3+ years
- Education
- PhD
Description
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
In this hybrid role, you will report to a Senior Staff Software Engineer.
You will:
- Partner with foundation model training teams to determine optimal data mixtures, training curricula, objectives, and other design choices that shape model capabilities.
- Design global-scale pipelines for dynamically updating and reusing data mixtures as our understanding of model behavior evolves and real-world datasets are continually ingested.
- Develop and deploy principled data-selection algorithms (e.g. influence estimation, proxy models, gradient similarity search) to find targeted subsets of data for fine tuning and RL.
- Run large-scale empirical studies linking pre-training data composition to downstream post-training performance, translating those scaling laws into optimized production training runs.
- Collaborate closely with behavior, perception, and evaluation teams to test these foundation models and measure their impact on the performance of the Waymo Driver.
You have:
- PhD in ML or related in AI/CS, or MSc with a strong academic publication record
- Strong statistical / ML knowledge
- Proficiency in Python
- 3+ years of experience with modern deep learning frameworks: JAX, TensorFlow/PyTorch
We prefer:
- Proven track record of deploying ML models to production environments
- Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning or imitation learning, transformer models, autoencoders and embeddings
- Autonomous driving experience
- C++ experience
The expected base salary range for this full-time position is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
