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# Staff Machine Learning Engineer - Deployment

- **Company:** Kodiak Robotics
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $200,000.0 - $265,000.0
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Software Debugging, Python (Programming Language), Machine Learning, Tensorflow, Pytorch, Deep Learning, Discretization, Information Technology, ONNX (Open Neural Network Exchange) Format, TensorRT
- **Published:** October 18, 2026
- **Apply:** https://www.juju.com/job/15_a63b2d6e5

## About the Role

* MS or PhD in Computer Science, Robotics, Machine Learning, or a related technical field, or equivalent practical experience.
 * 6+ years experience deploying machine learning or deep learning systems in production environments.
 * Proficiency in Python, C++ and modern ML frameworks such as PyTorch or TensorFlow.
 * Experience working with large-scale distributed training systems.
 * Solid understanding of optimization, and machine learning fundamentals.
 * Strong software engineering fundamentals including testing, debugging, and system design.
 * Ability to work collaboratively across teams to solve complex autonomy and robotics challenges.

## Description

* Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.
 * Help identify and achieve parity between onboard and deployed offboard models using validation on HIL
 * Collaborate with cross-functional teams including perception, planning, simulation, and autonomy infrastructure to integrate ML models into production systems.
 * Analyze real-world driving logs to identify edge cases and improve model robustness and safety.
 * Use profiling tooling to additionally help improve the train time for models by identifying and removing bottlenecks.
 * Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak's fleet.