AI/ML Engineer (Computer Vision)
About The Position
CACI is seeking an AI/ML Computer Vision Engineer with Agile methodology experience to join its BEAGLE Agile Solution Factory team supporting the Customs and Border Protection (CBP) client in Northern Virginia. The role develops AI/ML software and computer vision solutions for pilot projects and use cases, including custom object-detection models and live video inference pipelines. The engineer collaborates with prototyping teams, data scientists, video streaming engineers, software engineers, and system architects to deliver working applications on short timelines. The position involves designing scalable, highly available systems; integrating AI/ML, Big Data, and BI solutions; and optimizing computer vision models and pipelines for CBP full-motion video feeds. The role requires a U.S. citizen able to pass a CBP background investigation and at least seven years of related technical experience, including four or more years developing and deploying deep learning/computer vision models.
Requirements
- U.S. citizenship and ability to pass a CBP background investigation, including checks covering felony convictions during the past three years, illegal drug use during the past year, and misconduct such as theft or fraud during the past year.
- Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Electrical Engineering, or a related field with an AI/ML focus.
- At least 7 years of related technical experience, including at least 4 years developing and deploying deep learning/computer vision models, with a strong focus on object detection.
- Experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow and computer vision libraries such as OpenCV.
- Experience implementing and fine-tuning YOLO models, including Ultralytics YOLOv8/v9/v10 and 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 such as RTSP, HLS, or files, including frame-by-frame processing.
- Expert-level Python programming and ability to write clean, modular, optimized code.
- Experience with data curation, active learning, and using or managing annotation tools such as CVAT, LabelStudio, or Roboflow.
Nice To Haves
- Experience with multi-object tracking algorithms such as DeepSORT or ByteTrack.
- Familiarity with cloud-based AI infrastructure such as AWS SageMaker or EC2 GPU instances.
- Experience deploying models to edge devices such as NVIDIA Jetson or tactical hardware.
- Prior experience working with federal agency datasets or Customs and Border Protection.
Responsibilities
- Design, develop, and implement custom software solutions for AI/ML pilot projects and use cases.
- Work as a member of prototyping teams, supporting teammates and collaborating to deliver working software applications on short timelines.
- Analyze complex project problems and create innovative solutions involving technology, methodology, tools, and solution components.
- Participate in Agile delivery phases and ceremonies, including release and sprint planning, artifact creation, sprint testing, demonstrations, and retrospectives.
- Stay current with advancements in AI technologies, tools, and best practices.
- Design systems that scale horizontally and support high availability.
- Work with data science teams to integrate applications with AI/ML, Big Data, or BI solutions.
- Work independently on complex tasks with little direction or management oversight.
- Design, modify, and train custom YOLO architectures for the environment, resolutions, and challenges of CBP full-motion video feeds.
- Help architect a pipeline for ingesting, cleaning, and preprocessing production-recorded video data into a secure training and sandbox environment.
- Define annotation and labeling guidelines, manage dataset curation, and address class imbalance, varying weather conditions, and low-contrast environments.
- Optimize model inference speed and accuracy using hardware-acceleration toolkits such as NVIDIA TensorRT, DeepStream, and CUDA.
- Collaborate with video streaming engineers, software engineers, and system architects to integrate a live computer vision inference pipeline with the broader application.
Benefits
- Flexible time off benefit.
- Learning resources and learning and development opportunities.
- Healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
