Staff ML Engineer – Autonomous Driving AI Training & Inference

Rivian Automotive; Camden Town; Presencial; GBP 150.000 - 190.000; Jornada completa

Descripción de la vacante

Rivian is seeking a Staff Engineer to lead ML training and infrastructure within the Perception team. You will help build state-of-the-art ML infrastructure for training and inference in large autonomous driving models, and optimize performance across training and inference pipelines.

You will define cross-team technical strategies, elevate engineering practices, and benchmark modern tools and frameworks to push the capabilities of our self-driving technologies.

Formación

• PhD in CS/CE/EE, or equivalent 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.

Responsabilidades

• 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.

Conocimientos

PyTorch

TensorFlow

Jax

Transformer architectures

Distributed training

Model profiling

Educación

PhD in CS/CE/EE or equivalent industry experience

Herramientas

Model training framework

Descripción del empleo

Rivian is seeking a Staff Engineer to lead ML training and infrastructure within the Perception team. You will help build state-of-the-art ML infrastructure for training and inference in large autonomous driving models, and optimize performance across training and inference pipelines.

You will define cross-team technical strategies, elevate engineering practices, and benchmark modern tools and frameworks to push the capabilities of our self-driving technologies.