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# Senior Machine Learning Engineer, Perception LLM/VLM

- **Company:** Waymo LLC
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $204,000.0 - $259,000.0
- **Contract:** Permanent contract
- **Skills:** Computer Vision, Big Data, Computer Programming, Python (Programming Language), Machine Learning, Language Modeling, Motion Planning, Tensorflow, Data Streaming, Pytorch, Large Language Models, Deep Learning, Information Technology
- **Published:** September 1, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/85805600/1

## About the Role

* 5+ years of experience in Machine Learning, with a focus on large-scale model development (LLM, VLM, or similar foundation models).
 * Proven expertise in LLM/VLM pre-training, continual learning with large scale datasets.
 * Strong coding proficiency in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch).
 * Hands-on experience with model training, evaluation, and deployment in a production environment.
 * Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.

We prefer:

 * Experience in fine-tuning foundation models for autonomous driving or robotics applications
 * Familiarity with large-scale data curation and quality assurance processes for multimodal datasets.
 * Background in autonomous vehicle perception, motion planning, or decision-making systems.
 * Publications in top-tier machine learning or computer vision conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
 * PhD in a relevant field.

## Description

* Design, implement, and optimize large-scale continual pre-training pipelines for cutting-edge VLM foundation models.
 * Conduct research and development on novel pre-training techniques, focusing on efficiently integrating new, diverse, and multimodal data streams (e.g., visual data from different sensors) into existing models.
 * Develop and rigorously evaluate metrics and methodologies for measuring the performance, and transferability of continually pre-trained foundation models in the context of autonomous driving.
 * Stay current with the latest advancements in large language models, vision-language models, and continual learning, and translate relevant research into production-ready systems.


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