Location: Springfield, VA/St.Louis, MO
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.**
teKnoluxion provides the Defense and Intelligence Communities technical experts in the fields of Software & Systems Engineering, Enterprise Operations, and Cloud Services Management & Consulting. Our goal is not to simply support efforts, but to ignite a technology revolution, bridging the growing technology gap between the Government and commercial space.
Are you ready to test your abilities as a Machine Learning Engineer and team member in a sophisticated enterprise exploitation environment? Would you like to make an immediate and direct impact in your job? Join a dedicated team supporting the UDS contract at NGA.
What you get to do every day:
What skills do you need?
Clearance: 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:
Required Skills:
Demonstrated 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.
Demonstrated professional or academic experience building secure containerized Python applications to include hardening, scanning, automating builds using CI/CD pipelines.
Demonstrated professional or academic experience using Python to queryy 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.
Demonstrated 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.
Demonstrated professional or academic experience with version control systems such as Gitlab.
Demonstrated experience leveraging CUDA for GPU accelerated computing.
What is ideal?
Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
Demonstrated experience with OpenShift and container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
Demonstrated experience with Vision Transformers (ViT) such as DINO or DeiT.
Demonstrated academic or professional experience communicating methodological choices and model results.
Demonstrated experience with verification and validation test benches.
Demonstrated experience with Explainable AI (XAI) techniques.
Demonstrated experience with Open Neural Net Exchange (ONNX).
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