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Senior Staff Machine Learning Engineer, Perception

Waymo

$281,000 - $356,000
Dec 16, 2025
Mountain View, CA, US
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Waymo is looking to improve its autonomous driving technology by building the Waymo Driver, which requires advanced perception capabilities to safely deliver people to their destinations.

Requirements

  • Master’s degree or PhD in Computer Science, Engineering, or a related technical field
  • 8+ years of experience in ML-related software development
  • 6+ years of experience in ML-driven production systems that develops models with large-scale data, training, evaluation, and deployment
  • 4+ years of experience in a technical leadership role leading technical teams and setting technical directions
  • 3+ years of experience with computer vision models, or LLMs, or vision language models
  • Experience in LLM and / or multi-modality LM pretraining and fine-tuning, and their infrastructure
  • Experience in model distillation techniques and infrastructure

Responsibilities

  • Work closely with ML engineers and infrastructure teams to design, set the roadmap, and implement the multi-stage training system that builds the foundation models and onboard models
  • Optimize end-to-end training latency, to meet our release cadence while minimizing time-to-impact from new issues in the field to model update on the car
  • Solve large-scale training with multi-model, multi-task, and large models, with millions of miles of driving data
  • Provide technical leadership on the efficacy and efficiency of production critical models’ training system
  • Drive and accelerate collaborations between Perception, infra teams at Waymo, and Alphabet collaborators

Other

  • Master’s degree or PhD in Computer Science, Engineering, or a related technical field
  • 8+ years of experience in ML-related software development
  • Passion to drive engineering excellence and efficient model development through flywheel automation, while having direct technical experience in model quality development to achieve business goals
  • Agility in a fast-paced environment
  • Travel requirements not specified