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$11K
$88.2K
$135.5K
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Full-time
Re-posted 17 days ago
Job description
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.
You have:
- 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
#LI-hybrid
About Waymo
Sourced by ZipRecruiter
Industry
Internet and it
Company size
1,001 - 5,000 Employees
Headquarters location
Mountain View, CA, US
Year founded
2009