Mid-level Computer Vision Engineer focusing on remote sensing and GEOINT, responsible for designing, implementing, and optimizing CV algorithms and deep learning pipelines while owning key components of the solution.
Responsibilities
- Develop and implement computer vision algorithms for target detection, characterization, and tracking across single and multi-sensor data streams
- Build and maintain model training, evaluation, and deployment pipelines in Python or C++
- Apply deep learning techniques, including transformer-based architectures such as DINO, CLIP, and SAM, to image understanding tasks
- Integrate classical estimation methods like Kalman family filters with modern deep learning workflows to enable real-time development
- Contribute to GPU-accelerated model development using CUDA, RAPIDS, or vendor-specific inference runtimes
- Collaborate with multidisciplinary engineering teams to test, refine, and operationalize CV models for constrained compute or real-time environments
- Support the implementation of microservice based inference pipelines or containerized deployments under senior guidance
- Contribute to the architecture and implementation of novel single and multi-sensor platform detection and track fusion of targets
Requirements
- 3+ years of experience developing computer vision algorithms for detection, tracking, or sensor-based analytics in remote sensing or GEOINT contexts
- 1+ years applying deep learning to CV problems using transformer-based, self-supervised, or contrastive 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 to support real-time development
- Active TS/SCI clearance and willingness to undergo a polygraph examination
- Bachelor's degree in a STEM field
Technologies
- Python
- C++
- DINO
- CLIP
- SAM
- CUDA
- RAPIDS
- Kalman filters
- Kubernetes
Benefits
- Health benefits
- Life insurance
- Disability benefits
- Financial benefits
- Retirement benefits
- Paid leave
- Professional development
- Tuition assistance
- Work-life programs
- Dependent care
Nice if you have
- Experience with GPU programming, including CUDA or RAPIDS
- Experience modeling synthetic kinematic features for targets
- Experience with AI-augmented development workflows or multi-agent tools (Codex, Claude Code, OpenCode, etc.)
- Knowledge of modern software design patterns, including microservice design and Kubernetes orchestration
- Master's degree in Computer Science, Electrical Engineering, Computer Engineering, AI/ML, Physics, Mathematics, or a related field
Clearance
Applicants selected will undergo a security investigation and must meet eligibility requirements for access to classified information; TS/SCI clearance is required.
Compensation
Projected annual salary range is $69,300.00 to $158,000.00 (USD), with final figures determined by location, education, experience, and contract specifics. This estimate reflects Booz Allen's typical compensation range and total compensation package components.
Work model
Onsite: work conducted primarily at a Booz Allen office or customer facility, with collaboration in person as required by the role.
Identity statement
As part of the hiring process, an identity verification process using advanced biometrics and AI may be employed to ensure authenticity. Interview and assessment sessions may require on-camera participation, and photos may be used for identity verification and fraud prevention.
Candidate AI usage policy
AI is integrated into daily work at Booz Allen, with a commitment to responsible use. Use of AI or other tools to assist with interview responses is prohibited unless explicit permission is granted.
Work model notes
Onsite work involves collaboration with Booz Allen and client teams at facilities, while hybrid work may require periodic facility visits; remote roles may still entail occasional in-person engagements as needed.
Commitment to non-discrimination
All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, or any other status protected by applicable law.
