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NEXTMOVEFDE careers · United States
NT Concepts

Machine Learning Engineer

AI summary of the role

Machine Learning Engineer role at NT Concepts focused on taking computer vision models from research to production for national security missions.

What you’ll do

  • Support the full ML lifecycle, taking computer vision models from experimentation to containerized production microservices.
  • Work with mission partners to translate operational challenges into practical ML requirements.
  • Build and optimize MLOps pipelines for data prep, training, validation, deployment, and monitoring using MLflow, Kubeflow, GitLab CI/CD.
  • Train, fine-tune, and evaluate deep learning models for object detection, classification, segmentation, and tracking.

What you’ll bring

  • Active TS/SCI clearance (CI Polygraph preferred or eligible).
  • Professional experience developing and deploying ML models in production.
  • Strong Python skills and hands-on experience with PyTorch, OpenCV, TensorFlow, or NumPy.
  • Familiarity with Docker, Kubernetes, and ML platforms like MLflow, Kubeflow, or AWS SageMaker.

Technologies

PyTorch · OpenCV · TensorFlow · NumPy · MLflow · Kubeflow · AWS SageMaker · Docker · Kubernetes · GitLab CI/CD

About NT Concepts

Privately held defense and intelligence technology firm delivering data science, AI/ML, computer vision, and digital modernization for DoD and IC mission-critical programs.

Bootstrapped · 200–500 people

Source and classification

Internal deployment & tooling · Evidence for this classification:

We are seeking a Machine Learning Engineer with a passion for building mission-critical capabilities to join our talent network. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, explore What's Next with us. Mission Focus: Our machine learning teams bridge the gap between cutting-edge AI research and operational government missions. We are looking for engineers who can take machine learning and Computer Vision (CV) solutions from early research and prototyping all the way into stable, scalable production environments. In this role, you will help design, build, and deploy automated ML workflows that directly support national security analysts and operators. We embrace modern agile
More from the job description

We are seeking a Machine Learning Engineer with a passion for building mission-critical capabilities to join our talent network. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, explore What's Next with us. Mission Focus: Our machine learning teams bridge the gap between cutting-edge AI research and operational government missions. We are looking for engineers who can take machine learning and Computer Vision (CV) solutions from early research and prototyping all the way into stable, scalable production environments. In this role, you will help design, build, and deploy automated ML workflows that directly support national security analysts and operators. We embrace modern agile practices, a DataOps/DevSecOps/MLOps ethos to "automate-first," and modern cloud-native architectures. Clearance: Active TS/SCI required (CI Polygraph preferred or must be eligible to obtain) Location/Flexibility: Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available) Responsibilities Prototype to Production: Support the full machine learning lifecycle, taking computer vision models from experimentation and notebooks into containerized, high-throughput production microservices [... source excerpt omitted ...] cure cloud infrastructures. Optimization & Governance: Optimize inference performance, apply secure coding practices, and monitor models for drift and reliability once deployed. Qualifications Clearance: Active TS/SCI clearance. Hands-On Experience: Demonstrated professional experience developing, testing, and deploying machine learning models into real-world or production environments. Deep Learning & CV: Strong programming skills in Python and hands-on experience with deep learning frameworks (primarily PyTorch, OpenCV, TensorFlow, or NumPy). ML Lifecycle & MLOps: Practical familiarity with containerization (Docker, Kubernetes) and ML lifecycle/pipeline platforms (e.g., MLflow, [... source excerpt omitted ...] eMaker). Cloud & DevOps Foundations: Familiarity working in cloud environments (AWS, Azure, or GCP) and modern development practices (Git, CI/CD pipelines, Agile methodologies). Customer & Mission Mindset: Ability to understand the end-user's mission objectives, iterate based on user feedback, and clearly communicate technical approaches. Preferred / Desired Skills: Experience working within secure, air-gapped, or classified cloud environments (e.g., AWS GovCloud / C2S). Experience with synthetic data generation techniques or multi-modal models. Exposure to Large Language Models (LLMs) or generative AI workflows. Familiarity with distributed model training and GPU resource

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