Lead AI​/ML Engineer; Computer Vision

Job Title:

Lead AI/ML Engineer (Computer Vision)
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 Senior AI/ML Computer Vision Engineer with Agile methodology experience to join our BEAGLE (Border Enforcement Applications for Government Leading-Edge Information Technology) Agile Solution Factory (ASF) Team supporting the Customs and Border Protection (CBP) client located in Northern Virginia!

As the Senior AI/ML Engineer and Team Lead for our newly formed Computer Vision team, you will lead a dedicated 3-person pod focused on designing, training, and deploying custom, state-of-the-art YOLO models from scratch. Your team will process live Full-Motion Video (FMV) feeds to automatically detect and parse critical objects (roads, vehicles, people, and custom tactical assets). You will architect the offline training pipeline, define data curation and annotation standards for production-captured datasets, and guide two mid-level engineers in building high-performance, low-latency inference models.

• ·
  Technical Leadership: Lead a 3-person AI/ML engineering team, defining technical direction, sprint goals, code standards, and model evaluation metrics.
• ·
  Custom YOLO Architecture: Design, modify, and train custom YOLO architectures from scratch, optimized specifically for the unique environment, resolutions, and challenges of CBP's FMV feeds.
• ·
  End-to-End Pipeline Architecture: Architect the pipeline to ingest, clean, and pre-process production-recorded video data into a secure training/sandbox environment.
• ·
  Data Strategy: Define annotation/labeling guidelines, manage dataset curation, and implement strategies to handle challenges like class imbalance, varying weather conditions, and low-contrast environments.
• ·
  Performance Optimization: Optimize model inference speed (FPS) and accuracy (mAP, Precision, Recall) using hardware-acceleration toolkits (e.g., NVIDIA TensorRT, Deep Stream, CUDA).
• ·
  System Integration: Collaborate with Video Streaming Engineers, Software Engineers, and System Architects to integrate the live CV inference pipeline with the broader application.
• ·
  Agile Team Delivery: Act as the primary POC for the AI/ML pod, translating system requirements into technical tasking within our Agile/Scrum environment.

Required:

• · Must be a U.S. Citizen with the ability to pass a CBP background investigation. Criteria include, but are not limited to:
• o 3-year check for felony convictions
• o 1-year check for illegal drug use
• o 1-year check for misconduct such as theft or fraud
• ·
  Education: Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Electrical Engineering, or a related field with an AI/ML focus.
• ·
  Professional
  
  Experience:
  
  7+ years of related technical experience, with 4+ years of dedicated experience developing and deploying Deep Learning/Computer Vision models (with a heavy focus on object detection).
• ·
  Location: Local candidates must be available to work a hybrid schedule in Ashburn, VA.

• · Deep learning frameworks (
  Py Torch preferred, Tensor Flow) and Computer Vision libraries (
  OpenCV
  ).
• · Advanced implementation and fine-tuning of the YOLO family of models (e.g., Ultralytics YOLOv8/v9/v10, Custom YOLO backbones).
• · Training deep learning models from scratch, including custom anchor box design, loss function modification, and hyperparameter tuning.
• · GPU-accelerated computing using NVIDIA CUDA, cuDNN, TensorRT
  , or ONNX
• · Working with video streams (RTSP, HLS, files) and frame-by-frame processing.
• · Programming in Python (expert level) and writing clean,…