Staff Machine Learning Engineer, Tech Lead, Labeling Automation

Job description

Job responsibilities

• Architect and Scale Auto-Labeling: Lead the design and deployment of highly scalable auto-labeling pipelines that significantly improve data throughput and reduce our reliance on manual annotation bottlenecks.
• Build Robust Auto-Graders: Develop automated anomaly detection and quality evaluation systems (auto-graders) to assess annotation accuracy, detect regressions, and enforce rigorous quality standards across millions of…
• Train & Deploy SOTA Computer Vision Models: Train, optimize, and push into production advanced 2D and 3D computer vision models.
• Leverage Vision-Language Models (VLMs): Fine-tune, and deploy large VLMs and LLMs, utilizing prompt optimization and advanced post-training techniques (SFT, RL, etc.), to solve complex, open-set labeling and contextual…
• Drive Technical Direction: Act as a technical pillar for the Labeling organization. Set the long-term ML strategy, guide architectural decisions, and mentor senior and mid-level engineers.
• Collaborate Cross-Functionally: Work closely with Perception, Planner, and Simulation teams to align labeling capabilities with the evolving ML data needs of the Waymo Driver.

Job requirements

• 8+ years of professional experience in the field of software engineering and applied machine learning
• Experience programming in C++ or Python
• Experience building, evaluating, and deploying deep learning models for object detection, segmentation, and spatial tracking
• Experience in large model training, distributed computing, and scaling deep learning architectures using frameworks like PyTorch or TensorFlow
• Experience taking machine learning solutions through the entire lifecycle—from research and experimentation to robust, scaled production deployment