Machine Learning Engineer with Security Clearance
4 days left
- Employer
- Scuttlebutt Services
- Location
- Springfield, Virginia
- Salary
- Commensurate
- Posted
- Jan 02, 2025
- Closes
- Jan 26, 2025
- Ref
- 2874366760
- Role Type
- Engineer
- Career Level
- Experienced Career
- Education
- Bachelor
- Work Mode
- Onsite
- Contract Type
- Full Time
- Organization Type
- Government
Springfield, VA/St. Louis, MO - Salary Range 100k-185k (TS/SCI) Job Brief We are looking for highly energetic, TS-SCI cleared, IT professionals who are interested in joining our seasoned team of technologists. We are focused on driving significant enhancements in the efficiency and effectiveness of enterprise-wide IT operations and performing routine O&M for an IC agency. The program itself supports a broad range of IT enterprise services for end-users around the globe, with smaller project teams that focus on particular areas (i.e. Platform as a Service, Application Services, Cloud Computing, High Performance Computing, API Management, etc.). 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. Requirements 5+ years of relevant experience.
Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models for segmentation and object detection tasks using satellite imagery.
Professional experience building secure containerized Python applications including hardening, scanning, and automating builds using CI/CD pipelines.
Experience using Python to query and retrieve imagery from S3 compliant APIs and perform common image preprocessing using libraries like Boto3 and NumPy.
Experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) for object detection or segmentation tasks.
Experience with version control systems such as Gitlab.
Experience leveraging CUDA for GPU accelerated computing. Desired Qualifications and Skills Experience with the HuggingFace Transformers library and hub.
Experience with OpenShift and container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
Experience with Vision Transformers (ViT) such as DINO or DeiT.
Experience communicating methodological choices and model results.
Experience with verification and validation test benches.
Experience with Explainable AI (XAI) techniques.
Experience with Open Neural Net Exchange (ONNX).
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. Requirements 5+ years of relevant experience.
Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained foundation and computer vision models for segmentation and object detection tasks using satellite imagery.
Professional experience building secure containerized Python applications including hardening, scanning, and automating builds using CI/CD pipelines.
Experience using Python to query and retrieve imagery from S3 compliant APIs and perform common image preprocessing using libraries like Boto3 and NumPy.
Experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) for object detection or segmentation tasks.
Experience with version control systems such as Gitlab.
Experience leveraging CUDA for GPU accelerated computing. Desired Qualifications and Skills Experience with the HuggingFace Transformers library and hub.
Experience with OpenShift and container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
Experience with Vision Transformers (ViT) such as DINO or DeiT.
Experience communicating methodological choices and model results.
Experience with verification and validation test benches.
Experience with Explainable AI (XAI) techniques.
Experience with Open Neural Net Exchange (ONNX).