Staff ML Engineer - Training & Inference Infra

Rivian Automotive; City Of London; On-site; GBP 120,000 - 170,000; Full time

Job summary

Rivian Automotive in London is seeking a Staff Engineer - ML training and infrastructure to join the Perception team. You will help build and optimize ML infrastructure powering self-driving features across Rivian’s electric vehicles.

The role demands deep expertise in large-scale DL training, transformer acceleration, and distributed systems, with leadership shaping cross-team strategies and cutting-edge tooling.

Qualifications

• PhD in CS/CE/EE, or equivalent, in industry experience
• Deep knowledge of PyTorch, TensorFlow or Jax
• Knowledge of model training framework
• In-depth knowledge of transformer architecture and ways to accelerate the training and inference of transformer models
• Experience of performing large scale distributed training of models
• A track record of profiling models and doing detective work to improve model training and inference speed

Responsibilities

• Optimize the performance of Deep Learning training workload on NVIDIA GPU systems on a large scale
• Optimize the latency of model inference and model pre- and post-processing on onboard systems
• Design, train, and deploy large deep learning models that can leverage the vast amount of labeled and unlabeled data
• Define cross-team technical strategies, coding paradigms, and engineering best practices, elevating the technical baseline
• Benchmark and introduce modern technical tools, frameworks, and architectural patterns

Skills

PyTorch

TensorFlow

Jax

Transformer models

Distributed training

Model profiling

Education

PhD in CS/CE/EE

Tools

NVIDIA GPU systems

Job description

Rivian Automotive in London is seeking a Staff Engineer - ML training and infrastructure to join the Perception team. You will help build and optimize ML infrastructure powering self-driving features across Rivian’s electric vehicles.

The role demands deep expertise in large-scale DL training, transformer acceleration, and distributed systems, with leadership shaping cross-team strategies and cutting-edge tooling.