Senior Machine Learning Engineer, Multimodal Perception

Perception-focused MLE role dedicated to multi-modal sensor fusion, multi-task deep learning architectures for vehicle semantics and signal detection, dynamic high-resolution vision backbones, and large-scale automated data engines.

In this hybrid role, you will report to the Technical Lead Manager of the Special Vehicle Compliance team.

Architect, train, and optimize multi-task deep learning models (PyTorch / JAX) across multi-modal sensor streams.

Build automated data mining pipelines, active learning loops, hard-example curation, and auto-labeling systems.

Develop high-resolution vision architectures and spatial-temporal transformer backbones.

Leverage multimodal foundation models for automated data curation, synthetic edge-case generation, and failure triage.

Profile and optimize models for efficient onboard accelerator inference.

2–5+ years training and deploying production vision or multi-modal deep learning models.

Experience with multi-modal sensor fusion (Camera + LiDAR + Audio), multi-task learning (MTL), transformer architectures, and PyTorch / JAX.

Experience building large-scale data curation pipelines, active learning loops, and auto-labeling systems.

Fluency with modern AI developer tools and foundation model workflows for fast prototyping.

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.