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 customer relationships:  Run technical discussions, requirement discovery, demos, standing 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 results to high-level DoD and industry customers; author technical reports; publish 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 engineering:  Python (NumPy, scipy, pandas/polars), PyTorch (preferred) or TensorFlow, git, CI/CD pipelines, automated testing, and code quality practices. 
• MLOps  & deployment:  Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the edge (e.g., NVIDIA Jetson). 
• Communication & leadership:  Excellent technical communication, customer-facing experience, and proven ability to lead cross-functional efforts. 
• Education:
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