Software Engineer, ML Infrastructure, Optimization

Nuro
Mountain View, CA
On-site

Who this role is best for

Best suited to mid-level ML infrastructure engineers with expertise in optimization techniques and GPU ML compilers, working in autonomous vehicle technology.

Best fit for

  • Engineers experienced in ML optimization techniques like quantization and pruning.
    — “Experience with ML optimization techniques such as quantization and pruning
  • Developers proficient in Python with working knowledge of C++ and CUDA.
    — “Proficient in Python and working experience with C++ and CUDA
  • Candidates passionate about robotics and autonomous vehicle technology.
    — “You are passionate about accelerating the benefits of robotics

Things to consider

  • Requires experience with deep learning frameworks like PyTorch or TensorFlow.
    — “Working experience deep learning frameworks (like PyTorch, Jax, Tensorflow, Keras)

How to stand out

  • Highlight specific projects where you optimized ML models for deployment.
    — “Optimize Nuro’s autonomy stack with cutting-edge optimization techniques
  • Demonstrate experience with ML compilers and runtimes in past roles.
    — “Experience maintaining, profiling, and optimizing GPU ML compilers & runtimes
  • Showcase contributions to end-to-end ML solutions in autonomous systems.
    — “design and implement end-to-end learned ML solutions
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Optimize Nuro’s autonomy stack
  • Deploy optimized models on Nuro’s fleet
Typical background
2+ years of relevant experience in ML optimization infrastructure

Skills & requirements

Required

ML Optimization TechniquesQuantizationPruningML CompilersPythonC++CUDAPyTorchJaxTensorFlowKeras

Preferred

Nuro Driver™Autonomy Stack

Stack & domain

PythonC++CudaPyTorchJaxTensorFlowKerasAutonomous DrivingMachine LearningOptimization Techniques

About the role

Original posting from Nuro

Who We Are 

Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides.

Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.

With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.

Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors.

About the Role

The Autonomy ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots!

About the Work

Optimize Nuro’s autonomy stack with cutting-edge optimization techniques like 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.

About You

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.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP

Source: Nuro careers

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