AI/ML Engineer (Computer Vision)

CACI • Ashburn, VA

15h • Hybrid

About The Position

CACI is seeking a Senior AI/ML Computer Vision Engineer with Agile methodology experience to join their BEAGLE (Border Enforcement Applications for Government Leading-Edge Information Technology) Agile Solution Factory (ASF) Team, supporting the Customs and Border Protection (CBP) client in Northern Virginia. The role involves leading a 3-person Computer Vision team focused on designing, training, and deploying custom YOLO models from scratch to process live Full-Motion Video (FMV) feeds for object detection. Responsibilities include architecting the training pipeline, defining data standards, guiding junior engineers, and optimizing model performance for real-time inference.

Requirements

• Must be a U.S. Citizen with the ability to pass a CBP background investigation.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Electrical Engineering, or a related field with an AI/ML focus.
• 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).
• Experience with deep learning frameworks (PyTorch preferred, TensorFlow) and Computer Vision libraries (OpenCV).
• Experience with advanced implementation and fine-tuning of the YOLO family of models (e.g., Ultralytics YOLOv8/v9/v10, Custom YOLO backbones).
• Experience training deep learning models from scratch, including custom anchor box design, loss function modification, and hyperparameter tuning.
• Experience with GPU-accelerated computing using NVIDIA CUDA, cuDNN, TensorRT, or ONNX.
• Experience working with video streams (RTSP, HLS, files) and frame-by-frame processing.
• Expert level programming in Python and writing clean, modular, and optimized code.
• Experience with data curation, active learning, and experience using/managing annotation tools (e.g., CVAT, LabelStudio, Roboflow).
• Local candidates must be available to work a hybrid schedule in Ashburn, VA.

Nice To Haves

• Experience with multi-object tracking (MOT) algorithms (e.g., DeepSORT, ByteTrack).
• Familiarity with cloud-based AI infrastructure (AWS SageMaker, EC2 GPU instances).
• Experience deploying models to edge devices (NVIDIA Jetson, tactical hardware).
• Prior experience working with federal agency datasets or Customs and Border Protection (CBP).

Responsibilities

• 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, DeepStream, 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.

Benefits

• flexible time off
• robust learning resources
• comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior