Senior Staff ML Engineer: Autonomous Driving Pretraining

Watershed Ventures; Palo Alto (CA); On-site; USD 265,000 - 331,000; Full time

Job summary

Rivian seeks a Sr. Staff Machine Learning Engineer to lead pretraining efforts for its Large Driving Model, building the foundation layer for self-driving through scalable models and distributed training systems.

You will guide objectives across camera, LiDAR, radar, maps, and vehicle-state inputs, partnering with cross-functional teams to translate pretraining progress into real autonomy outcomes.

Qualifications

• B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Robotics, or a related field.
• 8+ years of experience building large-scale ML systems.
• Strong experience training large neural networks with distributed training frameworks.
• Deep understanding of transformers, representation learning, self-supervised learning, or foundation models.
• Strong PyTorch experience, including distributed training, mixed precision, and large-scale training pipelines.
• Strong engineering judgment and ability to lead ambiguous technical efforts from prototype to production impact.

Responsibilities

• Lead pretraining strategy for large-scale autonomy foundation models.
• Develop pretraining objectives for multi-sensor driving data.
• Study scaling trends across model size, data, compute, sensors.
• Build distributed training workflows for large models (FSDP, mixed precision).
• Collaborate with perception, prediction, planning, simulation, data, and ML infra teams.
• Develop evaluations for representation quality and downstream tasks.
• Mentor engineers and lead on architecture, stability, and evaluation.

Skills

Large-scale ML

Distributed training

PyTorch

Transformers

Self-supervised learning

Foundation models

Model pretraining

Distributed training frameworks

FSDP

Mixed precision

Education

B.S., M.S., or Ph.D. in Computer Science, ML, Robotics, or related field

Tools

FSDP

Checkpointing

Job description

Rivian seeks a Sr. Staff Machine Learning Engineer to lead pretraining efforts for its Large Driving Model, building the foundation layer for self-driving through scalable models and distributed training systems.

You will guide objectives across camera, LiDAR, radar, maps, and vehicle-state inputs, partnering with cross-functional teams to translate pretraining progress into real autonomy outcomes.