Job description

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 * * * The Opportunity: 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! Responsibilities: 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, 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. Qualifications: 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. 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). Desired: · 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). - What You Can Expect: A culture of integrity. At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation. An environment of trust. CACI values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality. A focus on continuous growth. Together, we will advance our nation s most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy. Pay Range : There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits. The proposed salary range for this position is: $103,800 - $218,100 CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.

Requirements

Must-haves

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
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.
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.

Nice-to-haves

Deep learning frameworks ( PyTorch preferred, TensorFlow) and Computer Vision libraries ( OpenCV ).
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).

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Platform: workday
Effort: long

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