Machine Learning Engineer for AI/ML Solutions

3 weeks ago


Springfield, Virginia, United States INflow Federal Full time
About INflow Federal

Founded in 2013, INflow Federal has established itself as a leader in Network Modernization, Cybersecurity, and Data Modernization. With over 50% of our workforce comprised of US Military Veterans, we bring invaluable experience and insight to steer our customers' success.

We boast extensive expertise in supporting Joint Force Mission Operations, serving prestigious federal government clients including the United States Navy (USN), United States Marine Corps (USMC), and Joint Forces. Our dynamic small business is committed to empowering employees and customers with emerging AI/ML technologies, enhancing operational efficiency and deepening understanding of their transformative potential.

About the Job

As a Machine Learning Engineer at INflow Federal, you will be at the forefront 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.

This role requires demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models for quick performance of segmentation and object detection tasks using limited training data from satellite imagery. You will also be responsible for building secure containerized Python applications, querying and retrieving imagery from S3 compliant APIs, and performing common image preprocessing using libraries like Boto3 and NumPy.

The successful candidate will possess a strong background in deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) like ResNet or U-Net for object detection or segmentation tasks using satellite imagery. Additionally, they will have experience with version control systems like Gitlab and leveraging CUDA for GPU accelerated computing.

A Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience is required, along with 2+ years of experience in the field.

Required Qualifications
  • Demonstrated experience applying transfer learning and knowledge distillation methodologies.
  • Experience building secure containerized Python applications.
  • Proficiency in querying and retrieving imagery from S3 compliant APIs.
  • Strong background in deep learning frameworks.
  • Experience with version control systems like Gitlab.
  • Leveraging CUDA for GPU accelerated computing.

Estimated Salary: $120,000 - $150,000 per annum.

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