Top Computer Vision Jobs in Boston, MA

Develop advanced algorithms for airborne optical signal processing in cluttered environments, focusing on detection and target classification using physics-based and AI/ML methods.

Design, implement, and optimize computer-vision and multimodal ML algorithms; acquire and manage truth data; run experiments and rigorous evaluations; use MLOps tools for reproducibility; integrate and transition models to production (cloud, on‑prem, or embedded); track research advancements and analyze field-test data.

Lead design, training, fine-tuning, evaluation, and deployment of vision, vision-language, and vision-language-action models for autonomous systems. Build scalable data pipelines, SFT workflows, and evaluation frameworks. Optimize models for embedded hardware (ONNX, TensorRT), collaborate cross-functionally, translate research to production, and mentor engineers.

Develop and implement radar-based perception and multi-target tracking algorithms for ADAS. Design extended object tracking and point-cloud processing, integrate algorithms into embedded real-time systems, perform validation and debugging, analyze test results, and collaborate with cross-functional teams to improve system performance.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

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.

Develop and train computer vision and visual representation pipelines for robotic manipulation (RGB, RGB-D, depth, segmentation, pose, keypoints). Build perception models to support RL and imitation policies, improve synthetic/real data pipelines, evaluate models on real robots, calibrate sensors, and collaborate with robotics and simulation engineers to iterate on models and data for robust deployment.

Develop advanced Vision-Language-Action models for robotaxis, leading data strategies and improving driving behaviors using machine learning infrastructure.

Design, develop, and deploy perception and AI features for autonomous vehicles. Train and evaluate models, optimize inference and GPU performance, integrate and validate robotics systems, prototype solutions, and maintain production code and CI/CD workflows.

Support creation and management of labeled medical image datasets for AI algorithms. Collaborate with software, ML, systems engineers and clinical partners to develop data used for automated cardiovascular image analysis. Work on-site in Sudbury, MA.