Machine Learning Engineer

Machine Learning Engineer Location: McLean, VA (hybrid); occasional travel to Durham, NC and customer sites About CoVar CoVar is a small AI/ML R&D software company with offices in Durham, NC and McLean, VA, that uses artificial intelligence to solve problems that matter. Our teams build AI/ML solutions that help the DoD detect enemies and threats, help biomedical researchers find new cures, and help monitor machinery to prevent injuries and environmental catastrophes. We are passionate engineers dedicated to pushing the bounds of what AI/ML can do in the real world. About the Role We’re seeking a Senior ML Engineer (Technical Lead) with deep hands-on expertise in machine learning and computer vision, who can also lead DoD-focused programs, own customer engagement, contribute to business development, and help grow and manage a local engineering team in McLean over time. You’ll lead end-to-end technical delivery – from data to deployment – while serving as the primary technical point of contact for our customers. This role is ideal for someone who enjoys building production-grade ML systems, mentoring engineers, and translating complex technical work into compelling customer outcomes. What You’ll Do Lead programs end-to-end: Scope requirements, set technical strategy and milestones, plan resourcing, manage risks, and deliver results for DoD-focused ML/CV projects. Own cu [... source excerpt omitted ...] ing meetings, and briefings with senior stakeholders; turn feedback into clear roadmaps. Stay deeply hands-on (50–70%): Build data pipelines, train/evaluate CV models, and write production code. Design, train, and optimize detection/segmentation/tracking models and custom computer-vision pipelines; handle imbalanced data, domain shift, and real-world constraints. Deploy models to production (typically on the edge), instrument for monitoring, and iterate with CI/CD. Contribute to business development: Write technical sections of proposals/white papers, help shape capture strategy, provide level-of-effort estimates, and present prototypes. Communicate and publish: Present resul [... source excerpt omitted ...] ublish novel work in classified/unclassified settings when applicable. Minimum Qualifications Experience: 5+ years designing, building, and deploying machine learning systems in production (8+ preferred). Strong track record leading technical delivery for complex projects. ML/CV expertise: Deep understanding of ML fundamentals (e.g., gradient descent, cross-validation, ROC/PR curves, confusion matrices, mAP). Computer vision experience with modern architectures (e.g., YOLO family, CenterNet, RetinaNet, Detectron2, ViTs, segmentation networks), augmentation strategies, and evaluation. Experience with data curation/annotation workflows and dataset quality control. Software eng