Location: St. Louis, MO/Springfield, VA

Security Clearance Required:  Active TS (SCI eligibility) clearance and eligibility to obtain a CI poly is required upon application for initial consideration **This position is not open for any clearance upgrades or sponsorship.**

What you get to do every day:

• Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities for improving analytic workflows and addressing key intelligence questions.
• You will be at the cutting edge of implementing State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM) for conducting image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets such as satellite and aerial imagery, full-motion video (FMV), ground photos, and OpenStreetMap.

Security Clearance Required:  Active TS (SCI eligibility) clearance and eligibility to obtain a CI poly is required upon application for initial consideration **This position is not open for any clearance upgrades or sponsorship.**

Education/Experience:

• Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
• 5+ years of professional experience

Required Skills:

• Experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models to quickly perform segmentation and object detection tasks with limited training data using satellite imagery.
• Professional or academic experience building secure containerized Python applications to include hardening, scanning, automating builds using CI/CD pipelines.
• Professional or academic experience using Python to query and retrieve imagery from S3 compliant API's perform common image preprocessing such as chipping, augment, or conversion using common libraries like Boto3 and NumPy.
• Professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
• Experience leveraging CUDA for GPU accelerated computing.
• Demonstrated professional or academic experience with version control systems such as Gitlab.

What is ideal?

• Professional or academic experience with the HuggingFace Transformers library and hub.
• Experience with OpenShift and container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
• Experience with Vision Transformers (ViT) such as DINO or DeiT.
• Academic or professional experience communicating methodological choices and model results.
• Experience with verification and validation test benches.
• Demonstrated experience with Explainable AI (XAI) techniques.
• Demonstrated experience with Open Neural Net Exchange (ONNX).
• Intelligence Community Experience preferred

• Recognizing great achievements do not go unnoticed by teKnoluxion through service anniversaries, spot awards, and employee referral bonuses
• You’ll join a growing organization of passionate, top-shelf, IT engineering professionals with extensive experience in actively developing the technology revolution in the Intelligence community
• Highly competitive benefits package that reflects our objective of employing top industry performers