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# Staff Machine Learning Engineer - VLM/LLM Evaluation

- **Company:** Waymo LLC
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $238,000.0 - $302,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, C++ (Programming Language), Computer Programming, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Large Language Models, Deep Learning, Generative AI, Information Technology, Machine Learning Operations
- **Published:** August 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ad40939a37beb0fe

## About the Role

* Master's degree or PhD degree in Computer Science, similar technical field of study, or equivalent practical experience
 * 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record
 * Experience with large scale distributed system
 * Proficient programming skills (eg: Python, C/C++)
 * Strong analytical and debugging skills

We prefer:

 * ML infra experience: training, evaluating and deploying ML models at scale
 * Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning
 * Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)

## Description

This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

You will:

 * Work with a creative team of people who help to build the state-of-the-art Foundation Models that are used throughout Waymo's systems, both onboard autonomous vehicles and offboard in simulation
 * Lead the development of end-to-end evaluation systems and benchmarks for Waymo Foundation models, encompassing the entire lifecycle from pretraining and supervised fine-tuning (SFT) to reinforcement learning (RL), for evaluating the quality, safety, and realism of embodied AI agents
 * Partner within and across organizations to land disruptive and innovative tech in production
 * Implement and extend large large scale data and evaluation pipelines


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