Staff ML Engineer - Vision-Language Foundations

Waymo; California (MO); Hybrid; USD 251,000 - 310,000; Full time

Benefits offered by this job

Annual bonus

Equity incentive

Benefits program

Job summary

Waymo seeks a Staff AI/ML leader to architect and scale foundation models for autonomous driving. Define data strategies, oversee pre-training, post-training, and evaluation, and partner across ML Infra, Perception, Behavior, and AI Foundation teams.

The role blends technical leadership with hands-on modeling, advancing VLMs, reasoning, and edge-case coverage. A PhD or equivalent, 8+ years in DL, and a track record of shipping large-scale ML systems are desirable.

Qualifications

• Master's degree in CS, AI, ML, or related field.
• 8+ years designing, training, and scaling DL models; 3+ years on LLMs/VLMs.
• Experience with foundation models lifecycle from data curation to distributed training.
• Proficient in Python, PyTorch, or JAX; scalable ML systems expertise.
• Ability to define roadmaps and lead multi-quarter, multi-team initiatives.

Responsibilities

• Drive technical strategy for massive multimodal pre-training data and domain adaptation.
• Design post-training pipelines (SFT, RLHF/RLAIF) to improve reasoning and instruction-following.
• Architect scalable VLM data flywheels to autolabel edge cases for onboard perception models.
• Establish training recipes and scaling laws; optimize architectures and token budgets.
• Lead cross-functional AI strategy across ML Infra, Perception, Behavior, and AI Foundation teams.
• Provide staff-level technical leadership and mentor senior engineers.

Skills

Deep learning

ML infrastructure

Distributed training

Leadership

Education

Master's degree in CS/AI/ML

PhD preferred

Tools

Python

PyTorch

JAX

Megatron

Job description

Waymo seeks a Staff AI/ML leader to architect and scale foundation models for autonomous driving. Define data strategies, oversee pre-training, post-training, and evaluation, and partner across ML Infra, Perception, Behavior, and AI Foundation teams.

The role blends technical leadership with hands-on modeling, advancing VLMs, reasoning, and edge-case coverage. A PhD or equivalent, 8+ years in DL, and a track record of shipping large-scale ML systems are desirable.