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.

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.

The Senior Machine Perception Researcher develops software for advanced space and defense systems, utilizing algorithms and embedded software in complex environments.

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.

Lead technical projects in computer vision and autonomy, managing a team, developing software solutions for robotic systems, and collaborating with stakeholders.

Lead development of multi-modal 2D/3D perception systems for warehouse robots, own dataset and data pipeline, deploy optimized models to NVIDIA Orin edge hardware, write production-grade Python/C++ code, mentor engineers, and drive model robustness via active learning and QA.