Cleared Computer Vision Scientist

The work: 

• Develop, train, finetune and evaluate computer vision models in a wide range of topics, including geospatial, biometrics, 3D vision, semantic extraction, etc. 

• Deploy, maintain, and optimize ML models and data processes in a production environment  

• Develop custom Computer Vision (CV) algorithms that translate into mission value 

• Create tools to provide feedback from production ML models and data processes  

• Assist in the development and optimization of computer vision models using deep learning frameworks (e.g., PyTorch, TensorFlow). 

• Collaborate with other scientists and engineers to build and deploy models for tasks such as object detection, image segmentation, classification, and tracking

• Stay up to date with the latest research and advancements in the field of computer vision and deep learning

• Participate in data collection, preprocessing, and augmentation processes to ensure high-quality datasets

• Conduct experiments, analyze results, and contribute to the improvement of model accuracy and efficiency

• Assist in the integration of computer vision algorithms into production systems and applications 

• Document code, methodologies, and experimental results

Here’s what you need: 

• Hands-on experience with computer vision libraries (e.g., OpenCV) and deep learning frameworks (e.g., PyTorch, TensorFlow)

• Proficiency with programming languages such as Python, C/C++ or Rust 

• Strong understanding of CNNs, transformers and other advanced architectures and their applications in computer vision tasks

• Strong analytical and problem-solving skills

• Ability to work collaboratively in a team environment and take direction from senior team members

• Hands-on experience with developing computer vision models at scale from inception to business impact 

• Design and develop custom/novel architectures, define use cases, and develop methodology & benchmarks to evaluate different approaches 

• U.S. Citizenship (No Dual citizenship)

Bonus points if you have:  

• Advanced Degree in computer science, technology, engineering, mathematics (STEM) related field, with Ph.D. preferred, but not required 
• Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC
• Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP
• Hands on experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment 
• Hands-on experience with other image modalities (SAR, IR, HSI, Lidar, Sonar) 

Security Clearance: 

• Active Top Secret or TS/SCI or TS/SCI with polygraph Clearance