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AI​/ML Engineer Ashburn, VA,

Job in Ashburn, Loudoun County, Virginia, 22011, USA
Listing for: CACI International Inc.
Full Time position
Listed on 2026-09-23
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 86000 - 181800 USD Yearly USD 86000.00 181800.00 YEAR
Job Description & How to Apply Below
## AI/ML Engineer Ashburn, VA, USApply Now Find out how well you match with this jobJob :
332363

Job Title:

AI/ML Engineer Job Category:
Information Technology Time Type:
Full time Minimum Clearance Required to Start:
None Employee Type:
Regular Percentage of

Travel Required:

Up to 10%
Type of Travel:
Local *
* * CACI is currently looking for a
** Mid-Level AI/ML Computer Vision Engineer
** to join our BEAGLE Agile Solution Factory (ASF) Team supporting the Customs and Border Protection (CBP) client located in Northern Virginia!

As a Mid-Level AI/ML Engineer on our Computer Vision team, you will work within a specialized 3-person pod dedicated to building custom object detection and classification models using the
** YOLO
* * framework. Your mission will be to process live and recorded Full-Motion Video (FMV) feeds, enabling automated parsing of entities like roads, vehicles, people, and terrain features. You will play a hands-on role in bringing raw production video into our secure training environment, curating datasets, training models, and deploying high-performance inference pipelines.### What you’ll get to do:
* ** Model Training & Experimentation:
** Train, fine-tune, and evaluate custom
** YOLO
* * object-detection models on proprietary datasets. Run experiments with different hyperparameters, augmentations, and model sizes to find the optimal balance of speed and accuracy.
* ** Data Engineering & Ingestion:
** Process, clean, and format raw video files recorded from production environments into high-quality datasets for training.
* ** Dataset Annotation & Curation:
** Manage the data annotation lifecycle, labeling images and video frames, verifying annotation quality, and generating synthetic data where needed.
* ** Inference Pipeline Development:
** Write Python scripts to parse video frames, feed them into inference engines, and export structured prediction data (JSON/Protobuf) representing detected objects.
* ** Model Evaluation:
** Generate performance reports, confusion matrices, and precision-recall curves to identify model blind spots and continuously improve detection capabilities.
* ** Collaborative Agile Delivery:
** Work closely with the Senior AI/ML Lead, video engineers, and developers in an Agile/Scrum framework to deliver production-ready code in short sprints.###
*
* Required:

*** Must be a U.S. Citizen with the ability to pass a CBP background investigation. Criteria include, but are 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
* *
* Education:

** College degree (B.S.) in Computer Science, Data Science, Software Engineering, or a related discipline.
* ** Professional

Experience:

** 3–5 years of software engineering or data science experience, with
** 2+ years of hands-on experience building/training Computer Vision models**.
* *
* Location:

** Must be available to work a hybrid schedule in Ashburn, VA.###
*
* Required:

*** Programming in
** Python
* * and using core machine learning libraries (Num Py, Pandas, Scikit-Learn).
* Hands-on experience with
** PyTorch
* * or Tensor Flow for training neural networks.
* Experience implementing
** YOLO** (e.g., YOLOv8/v9) for object detection, segmentation, or classification.
* Familiarity with image and video processing techniques using
** OpenCV
* * or FFmpeg.
* Data curation, formatting, and experience using data annotation platforms (e.g., CVAT, Label Img).
* Using
** Git
* * for version control and collaborating on shared codebases.
* Strong analytical skills, with a focus on benchmarking model performance (mAP, FPS, inference latency).###
*** Desired:
**** Familiarity with containerized development environments (
** Docker**).
* Experience with GPU execution…
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