CoVar

Aug 31, 2026

Machine Learning Engineer

HybridUnited States

McLean, Virginia, United States

PythonDocker

About the Role

Machine Learning Engineer

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.

Why This Role Matters

You’ll be a key technical leader in our McLean office – setting technical direction, building a local team, and ensuring our DoD partners see tangible mission impact from AI/ML solutions. If you thrive in high-impact environments where you can both build and lead, we’d love to talk.

Location: McLean, VA (hybrid); occasional travel to Durham, NC and customer sites

Visit us: covar.com

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.

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: B.S. in engineering, math, computer science, or related field; M.S./Ph.D. preferred.

Clearance: Eligibility for U.S. security clearance. This requires U.S. citizenship.

Preferred Qualifications (Bonus)

Prior Department of Defense project experience, including briefing senior stakeholders and navigating DoD acquisition processes.

Active Secret or TS/SCI clearance; experience working in classified environments.

Experience managing or mentoring engineers; contributing to hiring and performance development.

Experience with proposal writing (SBIR/STTR, RFPs), technical volume authorship, and live demos.

Experience with multi-sensor fusion, signal-processing, tracking, synthetic data generation, domain adaptation, or semi/active learning for data-limited environments.

Familiarity with edge hardware optimization, and performance profiling.

Open-source contributions, publications, or patents in ML/CV.

Benefits

Competitive salary, cash bonus, equity structure, and 401k with employer contributions

Excellent health care coverage, including dental and vision plans

Parental leave

Short-term and long-term disability insurance

Life insurance

Flexible work schedule

Tuition support

PTO and paid holidays

Languages

Machine Learning Engineer

About the Role

Why This Role Matters

About CoVar

What You’ll Do

Minimum Qualifications

Preferred Qualifications (Bonus)

Benefits

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