AI ML Engineer

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CDIT is seeking a Mid-Level AI/ML Computer Vision Engineer to support the BEAGLE Agile Solution Factory (ASF) team serving U.S. Customs and Border Protection (CBP) in Northern Virginia.

You will be part of a focused three-person computer vision pod building custom object detection and classification models with the YOLO framework. The team processes live and recorded Full-Motion Video (FMV) feeds to automatically identify roads, vehicles, people, and terrain features. This is a hands-on role: you will bring raw production video into a secure training environment, curate datasets, train and tune models, and deploy high-performance inference pipelines.

• Model Training & Experimentation: Train, fine-tune, and evaluate custom YOLO object detection models on proprietary datasets; experiment with hyperparameters, augmentations, and model sizes to balance speed and accuracy.

• Data Engineering & Ingestion: Process, clean, and format raw video recorded in production environments into high-quality training datasets.

• Dataset Annotation & Curation: Manage the annotation lifecycle, including labeling images and video frames, verifying annotation quality, and generating synthetic data when needed.

• Inference Pipeline Development: Write Python scripts that parse video frames, feed them into inference engines, and export structured prediction data (JSON/Protobuf) for detected objects.

• Model Evaluation: Produce performance reports, confusion matrices, and precision-recall curves to find model blind spots and drive continuous improvement.

• Agile Delivery: Partner with the Senior AI/ML Lead, video engineers, and developers in an Agile/Scrum environment to deliver production-ready code in short sprints.

• B.S. in Computer Science, Data Science, Software Engineering, or a related discipline.

• 5+ years of software engineering or data science experience, including 2+ years hands-on building and training computer vision models.

• Python programming with core ML libraries (NumPy, Pandas, Scikit-Learn).

• Hands-on experience training neural networks with PyTorch or TensorFlow.

• Experience implementing YOLO (e.g., YOLOv8/v9) for object detection, segmentation, or classification.

• Image and video processing experience with OpenCV or FFmpeg.

• Data curation and formatting, with experience using annotation platforms such as CVAT or LabelImg.

• Git version control and collaboration on shared codebases.

• Strong analytical skills with a focus on benchmarking model performance (mAP, FPS, inference latency).

• Willing to work on site 2–3 days per week in Ashburn, VA.

• U.S. Citizenship and ability to pass a CBP background investigation, which includes but is not limited to:

– 3-year check for felony convictions

– 1-year check for illegal drug use

– 1-year check for misconduct such as theft or fraud

• Containerized development environments (Docker).

• GPU execution environments and model export formats (ONNX, TensorRT).

• Multi-object tracking libraries.

• Agile tools such as Jira and Confluence.

CDIT places skilled professionals on mission-focused government programs and supports them throughout their engagement. This role offers direct, hands-on work on applied computer vision for a federal border security mission, within a high-impact team.

CDIT is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.