Top Computer Vision Jobs in Boston, MA

Develop, fine-tune, train, and optimize computer vision and machine learning algorithms. Manage experiments, data, testing, validation, and reproducibility using MLOps tools. Research emerging ML techniques, analyze field-test data, and transition algorithms into production across cloud, on-premises, and embedded environments. Collaborate with engineers and national security customers to deliver mission-critical AI and natural language processing capabilities.

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 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 (ONNX, TensorRT). Collaborate with researchers and engineers to translate ML research into robust, production-ready perception capabilities for defense platforms.

Build and ship computer vision and machine learning solutions using classical CV, vision models, VLMs, and LLMs. Responsibilities include identifying high-impact use cases, preparing datasets, training and evaluating models, developing monitored CV pipelines, and creating quality metrics and evaluation systems. The role requires strong Python experience, classical computer vision expertise, ML knowledge, and collaboration in a fast-moving startup environment.

Supports real-time computer vision and video software for surgical navigation. Develops and tests image processing, tracking, calibration, geometric computation, augmented-reality overlays, and GPU-accelerated features. The intern prototypes algorithms, documents work, participates in code reviews and agile practices, and learns regulated medical-device software development, verification, and traceability while completing a defined engineering project.

Develop and deploy production-grade 3D LiDAR and computer-vision perception systems for mobile robots. Own algorithms from sensor characterization through fleet deployment, while building AI agents and automated pipelines for data labeling, dataset curation, edge-case triage, and regression validation. Collaborate across controls and software teams, lead architecture and testing efforts, mentor engineers, and improve collision avoidance and autonomous behaviors across diverse operating environments.

Develop and lead software and computer vision algorithms for semiconductor inspection platforms. Responsibilities include system-level problem decomposition across optics, mechanics, electronics, and software; image processing, machine learning, calibration, segmentation, classification, and detection; software design, coding, testing, optimization, and debugging; cross-functional product development; architecture ownership, documentation, mentorship, and customer problem resolution. International travel to customer sites of at least 20% is required.

Develop and deploy computer vision and machine learning solutions for autonomous vehicle perception, including object and signal recognition. Build production software in Python and C++, integrate models with vehicle systems, process camera and LiDAR data, and create testing and evaluation tools. Train, optimize, and analyze AI models, debug algorithms, improve inference performance, and research emerging technologies for safer autonomous driving systems.

Build and maintain Python-based intelligent automation for healthcare revenue cycle management. Develop OpenCV and image-based RPA for legacy desktop and virtualized applications, OCR document extraction, and Selenium web automation. Integrate with EHR, billing, and payer systems; apply AI/ML techniques; use Azure services; and ensure HIPAA/HITRUST-compliant security, monitoring, documentation, and credential handling. Collaborate with technical and operations teams while independently delivering production automation modules.

Designs and owns a sensing integration platform that converts LiDAR and imagery detections into structured records, condition assessments, and automated workflows. Responsibilities include computer-vision and LiDAR-fusion integration, geospatial data modeling, connector and API architecture, multi-product roadmap planning, and production standards for testing, monitoring, security, and data quality. The role also establishes reusable technical patterns and guides AI-assisted engineering across product teams.