Machine Learning Engineer | TS/SCI

    • Blackspoke
  • Arnold, MO
  • Posted 20 days ago | Updated 5 hours ago

Overview

On Site
Full Time

Skills

Application development
SAFE
Analytical skill
Workflow
Art
Language models
Geospatial analysis
Video
Computer science
Machine Learning (ML)
Data Science
Computer vision
Training
Hardening
Continuous integration
Continuous delivery
Python
Amazon S3
NumPy
Deep learning
PyTorch
TensorFlow
.NET
Satellite
CGI
Version control
GitLab
CUDA
GPU
Orchestration
Kubernetes
Verification and validation
Artificial intelligence
Neural Network
Microsoft Exchange
Innovation
Marketing operations
Recruiting
Security management

Job Details

Job Description

Job Description

Own your opportunity to serve as a critical component of our nation's safety and security. Make an impact by using your expertise to protect our country from threats. Be part of an exciting opportunity to contribute to one of the nation's most critical intelligence organizations. Your work directly impacts national security and global issues, you will have the chance to contribute to missions that are of paramount importance to the United States and its allies, know that that the environments and programs you support are making a difference on a global scale. Our customers operate at the forefront of technology, dealing with some of the most advanced defense, geospatial, and intelligence systems in the world.

Machine Learning Engineer

Deliver simple solutions to complex problems as a Machine Learning Engineer at Blackspoke. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. With a career in application development, you'll make the end user's experience your priority and we'll make your career growth ours.

At Blackspoke, people are our differentiator. As a Machine Learning Engineer, you will help ensure today is safe and tomorrow is smarter. Our work depends on a TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in St. Louis, MO.

What you will be working on:
As a Machine Learning Engineer, you will:

  • 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.

What you will bring to us (Must):

  • Bachelor or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
  • 5+ years of experience in relevant fields.

Technical skills:

  • 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, including hardening, scanning, and automating builds using CI/CD pipelines.
  • Demonstrated professional or academic experience using Python to query and retrieve imagery from S3 compliant APIs and perform common image preprocessing such as chipping, augmenting, 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.

Skills and abilities desired:

  • 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).

What you will get:

  • The opportunity to work on critical high-impact projects that contribute to national security.
  • A high-growth environment with numerous opportunities for professional growth.
  • A collaborative team environment that values innovation and efficiency.
  • A competitive benefits package that underscores our commitment to attracting and retaining top talent.

Location: Arnold, MO
US Citizenship Required


Equal Opportunity Employer/Veterans/Disabled. Individuals with disabilities, including disabled veterans or veterans with service-connected disabilities, are encouraged to apply. If you need assistance applying outside of the online application, please contact recruiting@blackspoke.com for more information.
This Organization Participates in E-Verify
This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment.
Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9. E-Verify Works for Everyone For more information on E-Verify, or if you believe that your employer has violated its E-Verify responsibilities, please contact DHS.
Department of Homeland Security: 888-897-7781and E-Verify.gov
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