Lead ML Engineer, End-to-End Autonomous Driving

Rivian Automotive; Camden Town; On-site; GBP 90,000 - 130,000; Full time

Job summary

Rivian Automotive in the United Kingdom seeks an experienced Autonomy ML engineer to guide the architecture, implementation, and deployment of the Large Driving Model. You will lead multi-modal transformer-based systems and training pipelines at scale, collaborating with perception, planning, and simulation teams.

Ideal candidates have 5+ years in ML systems for robotics or autonomous agents, strong Python/C++ software skills, and a track record from research to production.

Qualifications

• BS/MS/PhD in Computer Science, Robotics, or a related field.
• 5+ years of experience building and deploying large-scale ML systems.
• Deep understanding of foundation models, self-supervised learning, and world models in robotics or simulation.
• Strong software engineering background, with fluency in Python and C++.
• Experience training and evaluating transformer models or end-to-end autonomous agents.
• Familiarity with real-time inference systems and autonomous vehicle constraints.
• Proven leadership in driving ML projects from research to production.

Responsibilities

• Developing technical strategy and architecture for end-to-end autonomous driving model.
• Developing multi-modal, multi-task transformer-based systems that support closed-loop autonomy.
• Collaborating with cross-functional teams across perception, planning, simulation, and ML infrastructure.
• Driving alignment between model capabilities and real-world deployment constraints (latency, robustness, validation).
• Publishing internal technical guidance and mentoring engineers across autonomy ML.

Skills

Large-scale ML systems

Python

C++

Transformer models

Real-time inference

Education

BS/MS/PhD in CS/Robotics

Job description

Rivian Automotive in the United Kingdom seeks an experienced Autonomy ML engineer to guide the architecture, implementation, and deployment of the Large Driving Model. You will lead multi-modal transformer-based systems and training pipelines at scale, collaborating with perception, planning, and simulation teams.

Ideal candidates have 5+ years in ML systems for robotics or autonomous agents, strong Python/C++ software skills, and a track record from research to production.