Jr Machine Learning Engineer

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INflow Federal

πŸ’΅ $100k-$150k
πŸ“United States

Job highlights

Summary

The job is for a Machine Learning Engineer at INflow Federal, where the employee will work on AI/ML solutions for the Department of Defense networks. They will be responsible for prototyping and implementing deep learning models using satellite imagery. The candidate should have experience with deep learning frameworks like PyTorch or TensorFlow, Python, and containerization.

Requirements

  • Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models
  • Demonstrated professional or academic experience building secure containerized Python applications
  • Demonstrated 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
  • 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
  • Bachelors or Masters Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree
  • 2+ years experience
  • Active DoD TS/SCI

Preferred Qualifications

  • 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)

Benefits

  • Opportunities to work on high-impact projects
  • Access to the latest technologies
  • A culture that thrives on creativity and collaboration

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