Computer Vision Software Engineer, Lead

About the role

You will architect and build advanced computer vision and multi-sensor fusion systems for GEOINT missions. This role involves creating deep learning models and GPU-optimized pipelines for real-time target tracking in operational environments.

Key facts

What you'll do

• Design and deploy deep learning models focused on sensor fusion and target tracking.
• Write and maintain production code in Python or C++.
• Optimize algorithm performance using GPU programming frameworks.
• Build architectures for single and multi-sensor detection and fusion.
• Manage CI/CD workflows using Docker, Kubernetes, or Jenkins.
• Apply Agile and extreme programming methods to solve client workflow challenges.

Requirements

• 6+ years of experience in computer vision algorithms for detection, tracking, or multi-sensor fusion in GEOINT or remote sensing.
• 2+ years of experience with deep learning using transformer-based or self-supervised architectures.
• Experience with GPU-accelerated development using CUDA or RAPIDS.
• Knowledge of classical tracking methods like Kalman or extended filters.
• Bachelor degree in a STEM field.
• Active TS/SCI clearance with willingness to undergo a polygraph.

Nice to have

• Master degree or Doctorate in CS, Electrical Engineering, Computer Engineering, AI/ML, Physics, or Mathematics.
• Experience with TensorRT, ONNX Runtime, or Triton Inference Server.
• Knowledge of synthetic data generation, scenario simulation, or kinematic target models.
• Experience with advanced fusion techniques such as particle filters, Bayesian fusion, or joint multi-sensor registration.
• Familiarity with cloud ML platforms like AWS GovCloud or Azure ML.
• Experience with ViT variants, DINO, CLIP, or SAM.
• Background in geospatial data formats and sensor phenomenology.

Skills & tools

• Python, C++, CUDA, RAPIDS, Kubernetes, Docker, Jenkins, Kalman Filters, Deep Learning, Transformer Architectures, CI/CD, Agile.

Practical notes

• Benefits include health, life, disability, financial, and retirement plans, plus tuition assistance and paid leave.
• Eligibility for benefits requires a minimum of 20 hours worked per week.
• Identity verification via biometrics and AI is required during the hiring process.
• Use of AI tools during interviews is prohibited without explicit permission.
• Camera usage is expected during virtual meetings and assessments.
• All qualified applicants receive consideration regardless of disability or veteran status.