Computer Vision AI Engineer

About the role

The opportunity is to join Booz Allen's growing team for space solutions as a Computer Vision AI Engineer. You will work on developing and implementing deep learning computer vision models, focusing on sensor fusion and target tracking. You will collaborate with multidisciplinary teams to design, develop, test, and deploy technical solutions in Python, C++, and Rust.

Responsibilities

• Develop and implement deep learning computer vision models, with a focus on sensor fusion and target tracking.
• Collaborate with multidisciplinary teams to design, develop, test, and deploy technical solutions in Python, C++, and Rust.
• Develop and maintain Fire Control Systems, ensuring robustness and accuracy in real-time applications.
• Utilize GPU programming, including CUDA or RAPID, to optimize the performance of computer vision applications.
• Contribute to the architecture and implementation of embedded systems programming using C, C++, or Rust.

Requirements

• 4+ years of experience in sensor fusion and target tracking.
• Experience in deep learning for computer vision, including the use of transformer-based models such as DINO, CLIP, or SAM.
• Experience in AI, data science, ML engineering, or software engineering.
• Secret clearance.

Qualifications

• Bachelor's degree in a STEM field.

Skills

• Experience with embedded systems programming in C, C++, or Rust.
• Experience in GPU programming, including CUDA or RAPID.
• Knowledge of modern software design patterns, including microservice design and orchestration in Kubernetes deployment.

Benefits

• 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.
• Recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values.

Pay

The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD).

Schedule

Work model varies depending on the role, which could be remote, hybrid, or onsite.