ML Infrastructure Engineer — Optimization & Deployment (Equity)

Nuro; California (MO); On-site; USD 160,000 - 241,000; Full time

Benefits offered by this job

Equity

Annual bonus

Benefits package

Job summary

Nuro is hiring for an Autonomy ML Infrastructure role. You will design, build, and deploy core ML infrastructure components for model life cycles across autonomy teams, optimizing pipelines and models for deployment on Nuro’s fleet of self-driving robots.

The role collaborates with behavior, perception, and mapping experts, focusing on quantization, pruning, and compiler-driven optimizations to accelerate safe navigation. Requires strong Python/C++ and DL framework experience.

Qualifications

• 2+ years of relevant experience in ML optimization infrastructure.
• Experience with ML optimization techniques such as quantization and pruning, and ML compilers.
• Experience maintaining, profiling, and optimizing GPU ML compilers & runtimes.
• Proficient in Python and working experience with C++ and CUDA.
• Working experience deep learning frameworks (like PyTorch, Jax, Tensorflow, Keras).
• Proficient in Python and working experience with C++.
• You are passionate about accelerating the benefits of robotics for everyday life.

Responsibilities

• Optimize Nuro’s autonomy stack with quantization, low precision inference, and model pruning.
• Work with autonomy engineers to optimize, validate, and deploy large language models.
• Develop and maintain a world-class model compiler framework, FTL.
• Write robust, high-quality software to increase our confidence in our vehicle’s ability to navigate safely on-road.
• Collaborate closely with machine learning domain experts and engineers across behavior, perception and mapping to design and implement end-to-end learned ML solutions.

Skills

ML optimization

Quantization

Pruning

ML compilers

Python

C++

CUDA

PyTorch

Jax

TensorFlow

Keras

GPU runtimes

Tools

CUDA

PyTorch

TensorFlow

Job description

Nuro is hiring for an Autonomy ML Infrastructure role. You will design, build, and deploy core ML infrastructure components for model life cycles across autonomy teams, optimizing pipelines and models for deployment on Nuro’s fleet of self-driving robots.

The role collaborates with behavior, perception, and mapping experts, focusing on quantization, pruning, and compiler-driven optimizations to accelerate safe navigation. Requires strong Python/C++ and DL framework experience.