Senior Staff ML Engineer: Post-Training LLMs for Autonomy

SupportFinity™; San Francisco (CA); On-site; USD 281,000 - 356,000; Full time

Benefits offered by this job

Discretionary annual bonus program

Equity incentive plan

Generous company benefits program

Job summary

Waymo is seeking a Senior Staff Software Engineer specializing in Model Post Training to advance post-training methods for LLMs used in autonomous driving. You will collaborate with research to translate breakthroughs into production-ready systems and provide technical leadership across ML, infra, and data teams.

The role focuses on raising the bar for training, evaluating, and deploying LLMs within the autonomous driving tech stack, shaping direction amid evolving research and real-world

Qualifications

• Demonstrated experience developing post-training methods for LLMs.
• Extensive experience with deep learning frameworks and large-scale model training.
• Ability to operate effectively under ambiguity and set direction amid evolving constraints.
• Translate research insights into production-ready post-training pipelines.
• Experience applying LLMs in safety-critical domains (e.g., autonomy, robotics).
• Excellent communication and collaboration skills.

Responsibilities

• Post-training for instruction following and CoT thinking in LLMs for autonomous driving.
• Collaborate with research teams to turn advances into production-ready systems.
• Provide technical leadership to influence ML, infra, and data teams.
• Raise the technical bar for training, evaluation, and deployment of LLMs in the stack.

Skills

Post-training methods for LLMs

Ambiguity management

Translating research into production

Excellent communication and teamwork

Experience applying LLMs in safety‑crs

Tools

PyTorch

JAX

Job description

Waymo is seeking a Senior Staff Software Engineer specializing in Model Post Training to advance post-training methods for LLMs used in autonomous driving. You will collaborate with research to translate breakthroughs into production-ready systems and provide technical leadership across ML, infra, and data teams.

The role focuses on raising the bar for training, evaluating, and deploying LLMs within the autonomous driving tech stack, shaping direction amid evolving research and real-world