Top Computer Vision Jobs in San Francisco Bay Area, CA

Develops and transfers AI research into real-world autonomous aircraft and vehicle systems. Evaluates multimodal perception models, builds prototypes, combines learned and classical computer vision methods, and optimizes capabilities for edge deployment. The role involves Python and C++ software, sensor fusion, model evaluation, robotics, and collaboration with researchers and autonomy engineers to deliver tested, documented production capabilities.

Lead the design, deployment, and operation of production-scale photogrammetry and 3D reconstruction systems. Own computer vision investigations, optimize pipelines for speed and reliability, integrate emerging 3D methods, establish observability standards, mentor engineers, guide technical execution, and expand AI-assisted development workflows.

Designs and maintains scalable AI/ML, computer vision, and MLOps systems for scientific imaging data. Develops deep learning models for segmentation, classification, phenotypic profiling, registration, and feature extraction; builds evaluation frameworks, cloud data pipelines, and high-performance GPU workflows. Collaborates with scientists, analysts, product leaders, and engineers to translate imaging needs into technical solutions across biomedical and clinical datasets.

Lead the architecture and technical strategy for high-fidelity machine learning perception models powering autonomous vehicle simulation ground truth. Build scalable foundation-model systems, optimize inference across petabyte-scale datasets, define quality and coverage roadmaps, align cross-functional stakeholders, and mentor perception engineers. The role requires deep expertise in computer vision, 3D perception, multimodal models, ML infrastructure, and production-scale inference.

Build and maintain production computer vision preprocessing pipelines for virtual try-on, including segmentation, pose estimation, human parsing, and body mapping. Validate inputs, benchmark and integrate vision models, evaluate performance on internal datasets, perform data quality checks, and collaborate with ML scientists to productionize research.

Research and develop autonomy algorithms for Skydio drones, including prototyping new approaches, implementing computer vision and intelligent-system features, assessing feasibility, and measuring software and hardware performance. The intern will own a project and collaborate with experienced computer vision and software engineers to advance autonomous flight capabilities and deploy research into products.

Architect and deploy multimodal 2D/3D object detection systems using camera, LiDAR, and radar. Build data collection, evaluation, and proprietary dataset pipelines; train, monitor, and improve production perception models; develop the perception roadmap; and mentor junior engineers. The role requires end-to-end perception stack experience, cross-functional leadership, Python proficiency, and advanced education in computer science, robotics, or deep learning.

Develop and evaluate computer vision and machine learning solutions using production image datasets from autonomous retail robots. Projects may involve object detection, OCR, barcode decoding, segmentation, dataset curation, model evaluation, and error analysis. Interns will build experimentation and production tools, write maintainable Python code, collaborate with technical teams, communicate results, and present their project at the end of the program.

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

Build and maintain AI foundations and production model services, including fine-tuning and deploying open-source models in GPU-backed infrastructure. Develop computer vision, image understanding, OCR, document layout analysis, and multimodal solutions for PDFs, images, and scanned documents. Optimize inference performance, resource utilization, throughput, and latency while debugging production systems and improving engineering standards.