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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Machine Learning Engineer, Tech Lead, Labeling Automation - **Company:** Waymo LLC - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $251,000.0 - $310,000.0 - **Contract:** Permanent contract - **Skills:** Computer Vision, C++ (Programming Language), Distributed Systems, Python (Programming Language), Machine Learning, Language Modeling, Object Detection, Tensorflow, Software Deployment, Software Engineering, Pytorch, Large Language Models, Deep Learning, Data Pipelines - **Published:** July 22, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/86623623/1 ## About the Role * 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 We prefer: * Experience building internal tooling for ML developers ## Description Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. As a Staff Software Engineer (L6) on the Labeling Team, you will lead the technical strategy for automating our data pipelines. You will build cutting-edge auto-labeling systems to drastically scale our throughput and develop intelligent auto-graders to guarantee exceptional data quality. This is a high-impact leadership role where you will train, deploy, and orchestrate state-of-the-art computer vision architectures and Vision-Language Models (VLMs) to solve complex semantic labeling challenges across our massive autonomous driving fleet. In this hybrid role, you will report to a Technical lead Manager, Staff Software Engineer. You will: * 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 labels. * Train & Deploy SOTA Computer Vision Models: Train, optimize, and push into production advanced 2D and 3D computer vision models. You will utilize architectures ranging from foundational zero-shot models like SAM (Segment Anything Model) and efficient real-time detectors like YOLO, to bespoke 3D perception and tracking 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 reasoning tasks. * 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. ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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