Computer Vision Engineer

Overview As a Computer Vision Engineer, you design, train, and deploy production-grade ML and computer vision models for real-time applications. You work with engineers and domain experts to deliver solutions that impact customers and end users. You own projects across the ML lifecycle and see your models deployed in real-world environments. This role offers high ownership and opportunities to shape scalable, production systems. Compensation / BenefitsCompetitive compensation and equity packageHybrid work environment based in Cambridge, MACollaborative and mission-driven engineering cultureOpportunity to work on challenging, real-world machine learning problemsHigh-impact role with significant ownership and visibility ResponsibilitiesDesign, train, and deploy ML and computer vision models for production applicationsDevelop object detection, image classification, tracking, anomaly detection solutionsPerform experimentation to improve model performance and accuracyOptimize models for scalability, reliability, and real-time inferenceBuild and maintain pipelines for training, evaluation, and deploymentCollaborate with software engineers, product teams, and customers to tackle technical challengesTroubleshoot and improve ML systems in productionStay current with emerging ML and CV technologies Key requirements5+ years of professional experience in ML, computer vision, or related fieldsStrong programming skills in PythonExperience with ML frameworks such as PyTorch, TensorFlow, OpenCV, YOLO, scikit-learn, or similarExperience with CV techniques including object detection, segmentation, classification, tracking, or image processingUnderstanding of supervised, unsupervised, and semi-supervised learning methodsStrong debugging, optimization, and problem-solving skillsExperience using Git and modern software development practicesBachelor’s degree in Computer Science, Engineering, Machine Learning, or a related fieldownership of projectscollaboration with cross-functional teamsproblem-solvingPythonPyTorchTensorFlow