Tech Lead Manager — ML Training & Inference Infra

Rivian Automotive; City Of London; On-site; GBP 110,000 - 170,000; Full time

Job summary

Rivian seeks a Tech Lead - Manager for ML training and infrastructure within the Perception team. You will shape state-of-the-art training and inference pipelines for large autonomous driving models and drive architectural decisions across the team.

You will optimize DL workloads on NVIDIA GPUs, improve latency, design and deploy large models, and ensure scalability, security, and maintainability.

Qualifications

• PhD in CS/CE/EE, or equivalent, in industry experience.
• Deep knowledge of PyTorch, TrensorFlow 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
• Drive architectural decisions, design reviews, and engineering standards across the team to ensure scalability, security, and maintainability.
• Identify technical dependencies and operational bottlenecks early, unblocking team members to maintain high execution momentum.
• Establish and enforce team guidelines for code reviews, testing, deployment, and operational excellence.

Skills

PyTorch

TensorFlow

Transformer architecture

Model training framework

Large-scale distributed training

Profiling models

Inference optimization

Education

PhD in CS/CE/EE or equivalent

Tools

NVIDIA GPUs

Profiling tools

Job description

Rivian seeks a Tech Lead - Manager for ML training and infrastructure within the Perception team. You will shape state-of-the-art training and inference pipelines for large autonomous driving models and drive architectural decisions across the team.

You will optimize DL workloads on NVIDIA GPUs, improve latency, design and deploy large models, and ensure scalability, security, and maintainability.