Top Computer Vision Jobs in Boston, MA

Design, develop, deploy, and support scalable AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Optimize model training and inference for cost, latency, throughput, and hardware utilization. Own complex AI architecture, reliability objectives, governance, security, and compliance while collaborating across engineering, research, product, and program teams. Lead technical reviews, shape foundational AI roadmaps, and mentor senior technical staff.

Design, train, fine-tune, evaluate, and deploy state-of-the-art vision, vision-language, and vision-language-action models for autonomous systems. Build scalable data pipelines, SFT workflows, evaluation frameworks, and optimize models for embedded hardware using ONNX and TensorRT. Collaborate with cross-functional teams to translate research into robust, production-ready perception capabilities for defense platforms.

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, 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.

Develop and evaluate computer vision, perception, SLAM, and deep learning algorithms for multi-robot systems. Responsibilities include dataset and pipeline development, benchmarking production data, deploying software to robot hardware, processing sensor data, running simulations, documenting experiments, and presenting results. Projects may address object detection, segmentation, pose estimation, collision avoidance, localization, sensor fusion, and AI planning.

Develop and prototype computer vision and machine learning solutions for robotic trailer unloading. Train and adapt models for perception tasks such as object detection, segmentation, grasp estimation, depth estimation, and anomaly detection. Troubleshoot real robotic systems, evaluate emerging robotics advancements, transition prototypes to product teams, communicate technical priorities, mentor junior engineers, and provide technical leadership on key projects.

Design and optimize computer-vision and robotics ML models for constrained edge devices, build large-scale training and fine-tuning pipelines, compress and deploy models to embedded accelerators, profile on-device inference for latency and accuracy, and write maintainable Python/C++ code while staying current on state-of-the-art techniques.

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.