- Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities for improving analytic workflows and addressing key intelligence questions. You will be at the cutting edge 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.
- 5+ years
- 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.
- 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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Machine Learning Engineer - Springfield, United States - Abile Group, Inc.
Description
Overview:
Abile Group has an exciting and challenging opportunity for a Machine Learning Engineer on a 10 year contract providing User Facing and Data Center Services supporting an Intelligence Community customer. All the personnel on the team will work together to support innovative design, engineering, procurement, implementation, operations, sustainment and disposal of user facing and data center information technology (IT) services on multiple networks and security domains, at multiple locations worldwide, to support the IC mission.
The right candidate will possess the below skills and qualifications and be ready to handle all responsibilities independently and professionally.
Responsibilities:Clearance Required: Active or Reinstateable TS/SCI required with ability to pass a CI Poly
Degree and Years of Experience: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
Required Skills:
Desired Skills:
Abile Group, Inc. was formed in July 2004 to partner with the Intelligence Community and their Contractors in the areas of Enterprise Analytics & Performance Management, IT & Systems Engineering and Program & Project Management. We have significant experience with the Federal Government and are an EDWOSB dedicated to our employees and clients. We are looking for high performing employees who enjoy providing advice and guidance along with solutions development and implementation support, crafted by combining industry best practices with the clients subject matter experience and Abiles breadth of expertise.
EEO Statement:Abile Group, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. Anyone requiring reasonable accommodations should email with requested details. A member of the HR team will respond to your request within 2 business days.
Please review our current job openings and apply for the positions you believe may be a fit. If you are not an immediate fit, we will also keep your resume in our database for future opportunities.