AI/ML Engineer (Computer Vision)

CACI International•Ashburn, VA

1d•$103,800 - $218,100•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 dedicated 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 automatic object detection. Responsibilities include architecting the offline training pipeline, defining data curation and annotation standards, and guiding junior engineers in building high-performance, low-latency inference models.

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).
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, modular, and optimized code.
Data curation, active learning, and experience using/managing annotation tools (e.g., CVAT, LabelStudio, Roboflow).

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.