Machine Learning Engineer

4 weeks ago

Springfield, Illinois, United States INflow Federal Full time

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our team at INflow Federal. As a Machine Learning Engineer, you will be responsible for designing and developing cutting-edge AI/ML solutions for the Department of Defense (DoD). Your expertise will be instrumental in empowering DoD customers with innovative data management and infrastructure solutions.

Key Responsibilities:

  • Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities for improving analytic workflows and addressing key intelligence questions.
  • Implement 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.
  • Collaborate with cross-functional teams to integrate AI/ML solutions into existing systems and workflows.

Requirements:

  • 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 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

Desired 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).

About INflow Federal:

INflow Federal is a defense contractor dedicated to empowering DoD customers with cutting-edge AI/ML solutions. Our team is passionate about merging the prowess of humans and machines to solve complex problems. We are committed to developing our people so they can lead our customers into the future of mission systems and operations.

Equal Opportunity Employer:

INflow Federal is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

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