The opportunity
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…
What you'll do
Be part of a world-class, high-performing research engineering team to: advance the state of the art of ultra realistic multi-agent simulations using foundation models.
Collaborate closely with the core Waymo Realism Modeling team in London and: Waymo Oxford to use large foundation models to improve sim realism.
Work at the intersection of data engineering, model development, and: simulations, and drive architectural decisions. Own large, complex systems, driving architectures and designs that meet technical and business objectives.
Design and scale large distributed systems covering the ML lifecycle,: supporting planet-scale dataset generation, model training, and evaluation.
Collaborate cross-functionally to derive performance and system-level: requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment.
+ years of professional software engineering experience, with at least 4: years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
What they're looking for
- Solid experience in the development and optimization of machine learning: infrastructure tools like DeepSpeed, PyTorch, TensorFlow, Ray, or similar frameworks.
- Strong understanding of state-of-the-art machine learning models and: algorithms such as autoregressive transformers and familiarity scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.
- Strong leadership skills with experience driving ambiguous problems: end-to-end, with a willingness and independence to pick up whatever knowledge to get the job done. Passionate about building infrastructure, libraries, tools, and pipelines for engineers and scientists.
- Excellent communication skills, both verbal and written, with the ability to: translate complex technical concepts for a broad audience.