The Opportunity

Join a mission‑focused engineering team building advanced computer vision (CV), multi‑sensor fusion, and detection and tracking capabilities for remote sensing and GEOINT environments. As a Mid‑Level Computer Vision Engineer, you will design, implement, and optimize CV algorithms and deep learning pipelines, contributing to operational systems used across national security missions. You will work closely with senior engineers while owning well‑defined components of the technical solution.

What You'll Work On: 

• Develop and implement computer vision algorithms for target detection, characterization, and tracking across single‑ and multi‑sensor data

• Build and maintain model training, evaluation, and deployment pipelines in Python or C++

• Apply deep learning approaches, including transformer‑based architectures such as DINO, CLIP, or SAM, to image understanding problems

• Integrate classical estimation methods, such as Kalman‑family filters with modern deep learning workflows to support real‑time algorithm development

• Contribute to GPU‑accelerated model development using CUDA, RAPIDS, or vendor‑provided inference runtimes

• Collaborate with multidisciplinary engineering teams to test, refine, and operationalize computer vision models for constrained compute or real‑time environments

• Support the implementation of microservice‑based inference pipelines or containerized model deployments under senior guidance

• Contribute to the architecture and implementation of novel single and multi-sensor platform detection and tracking algorithms and track fusion of targets

Join us. The world can’t wait. 

You Have:  

• 3+ years of experience developing computer vision algorithms for detection, tracking, or sensor‑based analytics in remote sensing or GEOINT‑relevant environments

• 1+ years of experience applying deep learning to CV problems using transformer‑based, self‑supervised, or contrastive learning architectures, such as DINO, CLIP, or SAM

• Experience building pipelines in Python or C++ for algorithm development, training, evaluation, or deployment

• Experience with GPU‑accelerated workflows

• Experience with classical tracking and estimation methods, such as Kalman or extended Kalman filters, supporting real‑time development needs

• Active TS/SCI clearance; willingness to take a polygraph exam

• Bachelor's degree in a STEM field

Nice If You Have:  

• Experience in GPU programming, including CUDA or RAPIDs

• Experience with developing synthetic modeling of Kinematic target features 

• Experience with AI‑augmented development workflows or agentic tools, such as Codex, Claude Code, or OpenCode or other multi-agent approach

• Knowledge of modern software design patterns, including micro-service design and orchestration in Kubernetes deployment

• Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, AI/ML, Physics, Mathematics or other related field

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.

• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.

• Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.