Machine Learning Engineer | TS/SCI

at  Blackspoke

Own your opportunity to serve as a critical component of our nation’s safety and security. Make an impact by using your expertise to protect our country from threats. Be part of an exciting opportunity to contribute to one of the nation’s most critical intelligence organizations. Your work directly impacts national security and global issues, you will have the chance to contribute to missions that are of paramount importance to the United States and its allies, know that that the environments and programs you support are making a difference on a global scale. Our customers operate at the forefront of technology, dealing with some of the most advanced defense, geospatial, and intelligence systems in the world.
Deliver simple solutions to complex problems as a Machine Learning Engineer at Blackspoke. Here, you’ll tailor cutting-edge solutions to the unique requirements of our clients. With a career in application development, you’ll make the end user’s experience your priority and we’ll make your career growth ours.
At Blackspoke, people are our differentiator. As a Machine Learning Engineer, you will help ensure today is safe and tomorrow is smarter. Our work depends on a TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in St. Louis, MO.

TECHNICAL 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, including hardening, scanning, and automating builds using CI/CD pipelines.
• Demonstrated professional or academic experience using Python to query and retrieve imagery from S3 compliant APIs and perform common image preprocessing such as chipping, augmenting, 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.

SKILLS AND ABILITIES DESIRED:

• 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).

Please refer the Job description for details