Role Summary

We are seeking a Sr. Staff Machine Learning Engineer to lead model pretraining efforts for our Large Driving Model, an end-to-end autonomy model that learns from large-scale, multi-sensor driving data.

This role is focused on building the foundation model layer for self-driving: scaling larger models, improving pretraining objectives, understanding scaling laws, and developing the distributed training systems needed to train models across massive real-world and simulated datasets.

This is an ideal role for someone excited by the intersection of large-scale ML, autonomous driving, multi-modal representation learning, and high-performance distributed training.

Responsibilities

• Lead technical strategy for pretraining large-scale autonomy foundation models.
• Develop pretraining objectives for multi-sensor driving data, including camera, LiDAR, radar, maps, route, and vehicle-state inputs.
• Study scaling trends across model size, data scale, compute, sensor mix, and downstream autonomy performance.
• Build and improve distributed training workflows for large models, including FSDP, mixed precision, checkpointing, and training performance optimization.
• Partner with perception, prediction, planning, simulation, data, and ML infrastructure teams to connect pretraining progress to real autonomy outcomes.
• Develop evaluations that measure representation quality, downstream task performance, and closed-loop behavior.
• Mentor engineers and provide technical leadership on model architecture, training stability, scaling, and evaluation.

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.

Pay Disclosure

The salary range for this role is $265,000 - $331,000 for California based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.

The successful candidate may be eligible for annual performance bonus and equity awards.

We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian's 401(k) Plan and Employee Stock Purchase Program if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com.

Please note that we are currently not accepting applications from third party application services.