Top Computer Vision Jobs in San Francisco Bay Area, CA

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

As a Staff Software Engineer, you will lead the development of computer vision systems for sidewalk inspection, overseeing model lifecycle, system architecture, and mentoring while improving deployment practices.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

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.

As a Computer Vision Applied Research Scientist, you'll design novel architectures for understanding construction drawings, conduct end-to-end experiments, and transition models to production. You'll collaborate with others to improve accuracy and address real-world issues in AI applications for construction.

Lead the 3D Mapping team in designing ML models and algorithms for 3D perception and mapping, coordinating with cross-functional teams and driving development metrics.

Lead rapid prototyping of PoC research in computer graphics, computer vision, and machine learning to evaluate algorithms for production. Conduct R&D in human modeling and simulation, camera and image‑sensor simulation, and face/pose tracking for VR/AR hardware. Develop data-generation pipelines using graphics APIs and 3D tools, and implement ML systems with TensorFlow/PyTorch to support immersive AR/VR experiences.

Own and develop the end-to-end robot perception stack and high-reliability manipulation policies. Research, deploy, and iterate transformer/diffusion and other learned policies on real hotel robots, handle multimodal sensor data, debug field failures, and optimize models for real-time (~10 Hz) inference on constrained edge hardware.

Develop and productionize photogrammetry and radar image-formation pipelines for large-scale 3D reconstruction. Improve pipeline stages (bundle adjustment, dense matching, point clouds, geo-referencing), optimize storage and databases for 3D geospatial data, and contribute to data infrastructure, analytics, and delivery systems for satellite-derived products.