Video Analytics Engineer

Confidential

Sterling, Virginia permanent

Posted: April 29, 2026

Job Description

We are looking for a Video Analytics Engineer to support development and implementation of computer vision and deep learning models to analyze video data, often focusing on object detection, tracking, and behavior analysis. The video Analytics Engineer would work with our team to build, develop and deploy image classification, object detection, video understanding, and imagery analysis services.

Key Responsibilities would include, but are not limited to:

Test Planning & Execution: Design and execute test cases for video analytics systems, covering functionality, performance, and integration testing in both lab and real-world environments. The engineer will support COTS and customized video analytics software.

AI/Model Validation: Evaluate the performance of computer vision models (object detection, tracking) using datasets, validating against expected metrics.

Defect Detection & Analysis: Identify, reproduce, and report software bugs, focusing on issues like false positives, missed detections, and tracking failures.

Scenario Testing: Create complex, real-world scenarios (e.g., varying lighting, crowd densities, weather conditions) to test algorithm robustness.

Automation: Develop and maintain automated test scripts (Python/Bash) to streamline testing and validate video pipelines.

Collaboration: Work with developers to analyze logs, investigate system behavior, establish integration requirements and improve AI model accuracy. Collaborating with software engineering teams to integrate models into production systems

Skills Required:

US Citizens with an Active Secret Clearance

Technical Expertise: Experience with computer vision tools like OpenCV, YOLO, PyTorch, or TensorFlow. Past successful experience (1-3 years) in applying machine learning and deep learning to solve computer vision and/or video analysis problems.

Programming Skills: Proficiency in Python, C++, or Java for scripting and test automation.

Video Technology Knowledge: Understanding of video formats, codecs (H.264/H.265), and streaming protocols.

Analytical Abilities: Excellent analytical skills to troubleshoot complex issues, evaluate video performance, and interpret system logs independently.

Environment Familiarity: Experience with Linux systems, networking protocols, and edge devices (e.g., NVIDIA Jetson)

Location:

The Video Analytics Engineer will report daily on site to our office in Sterling, VA.

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