Computer Vision Software Engineer, Senior

Booz Allen Hamilton•Dayton, OH

2h•$112,800 - $257,000•Remote

About The Position

As a Senior Computer Vision Engineer, you will design, develop, and optimize advanced computer vision and multi-sensor fusion algorithms supporting GEOINT-mission workflows. You will lead the development of deep learning models, real-time tracking systems, and GPU-accelerated pipelines deployed in operational environments. You will shape next-generation tools that integrate imaging physics, ML-based behavior inference, and multi-sensor fusion. You’ll join a collaborative technical delivery team where you’ll contribute to secure, reliable, user-centric tools that accelerate mission outcomes.

Requirements

6+ years of experience developing computer vision algorithms for detection, tracking, or multi-sensor fusion in remote sensing or GEOINT-relevant environments
2+ years of experience applying deep learning to computer vision problems using transformer-based or self-supervised architectures
Experience implementing model pipelines in Python or C++, including training, evaluation, and deployment workflows
Knowledge of GPU-accelerated development using CUDA, RAPIDS, or GPU programming frameworks
Experience with administration of continuous integration / continuous deployment (CI/CD) pipelines using Kubernetes, Docker, or Jenkins
Experience with Agile methodology, extreme programming, software engineering, product management, and software products, and with acquiring client requirements and resolving workflow problems through automation optimization
Knowledge of classical tracking or estimation methods, such as Kalman or extended filters, to support real-time algorithm development
Ability to design, test, and optimize algorithms for operational performance in constrained computing environments such as multi-GPU servers or cloud
TS/SCI clearance
Bachelor’s degree in a STEM field

Nice To Haves

Experience with GPU-accelerated deep learning, including CUDA kernel development, TensorRT optimization, RAPIDS, or distributed multi-GPU training
Experience developing synthetic data, kinematic target models, or scenario simulation tools to support algorithm training or evaluation
Experience with advanced estimation, tracking, and fusion techniques such as joint multi-sensor registration, Bayesian fusion, particle filters, or deep multi-object tracking pipelines
Knowledge of geospatial data formats, sensor phenomenology, or remote-sensing exploitation workflows
Experience with MLOps or scalable deployment systems, including Docker, Kubernetes, ONNX Runtime, Triton Inference Server, or similar
Experience building or optimizing microservice architectures or distributed systems for real-time data processing
Experience integrating CV models into edge, embedded, or latency-constrained operational environments
Experience with transformer-based vision architectures beyond DINO / CLIP / SAM such as ViT variants or self-supervised multi-modal encoders
Experience with cloud ML platforms such as AWS GovCloud, Azure ML, or on-premises GPU clusters
Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, AI / ML, Physics, Mathematics or other related field preferred
Doctorate degree in Computer Science, Electrical Engineering, Computer Engineering, AI / ML, Physics, Mathematics or other related field a plus

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 or C++
Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision applications
Contribute to the architecture and implementation of novel single and multi-sensor detection and tracking and fusion of targets