Top Computer Vision Jobs in San Francisco Bay Area, CA

Develop, train, and optimize computer vision and ML models (particularly video-based safety) using petabyte-scale camera and sensor data. Deploy and optimize models for backend and edge inference, collaborate with cross-functional teams, and translate customer needs into scalable ML/CV solutions.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

Join Pakket to develop computer vision systems for warehouses, deploying solutions and shaping both product direction and company goals. You'll work hands-on with real-world operations.

Customer-facing ML engineer who develops, validates, and deploys 2D/3D computer-vision models on CT data for defect detection, dimensional analysis, anomaly detection, and process control. Responsibilities include scoping projects with customers, end-to-end model lifecycle (training, deployment, monitoring, retraining), collaborating with product and engineering to productize solutions, and producing technical documentation. ~30% travel to customer sites.

Lead and execute perception R&D and engineering for factory robots: define multi-year roadmap, architect perception pipelines (detection, segmentation, 6-DoF pose, scene understanding), drive sensor fusion and calibration, establish data/model workflows and deployment practices, integrate with planning/control, hire and mentor engineers, and evaluate research for production adoption.

The role involves training and developing large-scale image and video models, optimizing data pipelines, and conducting experiments in a high-performance computing environment.

Design and develop AI software for autonomous robotics, focusing on computer vision and VLA models, while collaborating across functions.

Design, train, and deploy large-scale computer vision and perception models (semantic segmentation, 4D geometry, preference models) for cloud and on-prem systems. Build data pipelines, annotation and evaluation tooling, validate models for field reliability, and ship production-grade features frequently. Senior roles lead architecture and experimentation; Staff roles own roadmaps for offboard perception models.

The Technical Lead for Computer Vision will implement advanced algorithms, mentor engineers, and optimize code in C++ and Python while collaborating across teams.

Design and prototype state-of-the-art visual encoders and multimodal representations; train billion-scale models on GPU clusters; build visual reasoning and retrieval tools; collaborate on text-to-image and VLM projects; mentor junior researchers; publish research and ship models to production.