Computer Vision / Machine Learning Engineer

Jobs / Computer Vision / Machine Learning EngineerComputer Vision / Machine Learning EngineerContractorAbout the RoleComputer Vision / Machine Learning Engineer (Contract)Contract Length: 6 monthsWork Arrangement: Hybrid (onsite 3 days/week in Greater Boston)Computer Vision / Machine Learning Engineer to support an active, production-focused initiative. This role is centered on improving detection and tracking accuracy for object-counting systems operating in real-world, high-throughput environments.The ideal candidate has hands-on experience building and deploying computer vision models, working with multimodal sensor data, and optimizing inference pipelines for edge deployment.What You'll Work OnEnhancing object detection, segmentation, and tracking accuracy in operational systemsDeveloping and deploying models into validation and pre-production environmentsImproving real-time performance and reliability on edge hardwareKey ResponsibilitiesModel Development: Train, validate, and deploy computer vision models, with an emphasis on instance segmentationTracking & Fusion: Implement tracking approaches that combine color and depth data to maintain object persistence across framesData Quality: Support data curation efforts and audit external annotations to ensure high-quality ground truthPerformance Optimization: Tune inference pipelines for low-latency execution on edge platformsTechnical EnvironmentComputer Vision & ML: Instance Segmentation, Object TrackingSensor Data: RGB + Depth (basic multi-sensor fusion)Edge & Optimization: NVIDIA-based edge hardware, TensorRT or similar acceleration toolsQualificationsProven experience delivering production-grade ML or CV systemsStrong software engineering fundamentals (version control, testing, CI/CD)Experience deploying models beyond experimentation into real environmentsAbility to meet strict accuracy and performance benchmarksComfortable working within cloud-only data environments with controlled access policiesNice to HaveExperience optimizing models for edge or embedded systemsFamiliarity with real-time or near–real-time vision pipelinesBackground in industrial, robotics, or high-volume operational settings #J-18808-Ljbffr