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Machine Learning Engineer

Pay
USD 120,336–180,504/yearAnnual period assumed — pay source
Virginia Pay Range $120,336—$180,504 USD About NT Concepts
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

Before you apply

Work authorization
Citizens onlyClearance: Active TS/SCI clearance

What you’ll work on

Full posting
  • Move computer vision models from notebooks into containerized production microservices

  • Build and maintain ML pipelines for data prep, training, deployment, and monitoring

  • Train, fine-tune, and evaluate deep learning models for vision tasks

  • Integrate ML models into enterprise systems and secure cloud infrastructure

  • Optimize inference performance and monitor deployed models for drift

From the employer’s posting
taking computer vision models from experimentation and notebooks into containerized, high-throughput production microservices
Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring
Train, fine-tune, and evaluate deep learning algorithms for computer vision tasks
integrate ML models cleanly into larger enterprise systems and secure cloud infrastructures
Optimize inference performance, apply secure coding practices, and monitor models for drift and reliability once deployed

What you’ll bring

All qualifications

Core experience

  • Hands-On Experience: Demonstrated professional experience developing, testing, and deploying machine learning models into real-world or production environments.
  • 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.
  • Familiarity with distributed model training and GPU resource management.
Qualification wording
Hands-On Experience: Demonstrated professional experience developing, testing, and deploying machine learning models into real-world or production environments.
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.
Familiarity with distributed model training and GPU resource management.

About NT Concepts

Founded in 1998 and headquartered in the Washington DC Metro area, NT Concepts is a private, mid-tier company with clients spanning the Intelligence and Defense communities.

In the employer’s words · Read in context

Apply at NT Concepts

Posting record

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Status in our records
Live
First seen by us
Sep 6, 202660 days ago
Recorded sightings
30
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Lower than most similar jobs

$120K–$181K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 60

Similar jobs usually come down between day 6 and day 70.

From 4,515 similar postings that came down. Coming down is not always a hire.

NT Concepts is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • AWS
  • Azure
  • Docker
  • GCP
  • Kubernetes
  • MLflow
  • SageMaker
  • NumPy
  • PyTorch
  • TensorFlow
  • Python
Where the posting names them
- 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, Kubeflow, AWS SageMaker). - Cloud & DevOps Foundations: Familiarity working in cloud environments (AWS, Azure, or GCP) and modern development practices (Git, CI/CD pipelines, Agile methodologies).
- ML Lifecycle & MLOps: Practical familiarity with containerization (Docker, Kubernetes) and ML lifecycle/pipeline platforms (e.g., MLflow, Kubeflow, AWS SageMaker). - 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.
- Mission Alignment: Work closely with mission partners, domain experts, and technical teams to understand real-world operational challenges and translate them into practical ML requirements. - MLOps & Pipeline Automation: Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring using modern tools (such as MLflow, Kubeflow, and GitLab CI/CD). - Model Development & Tuning: Train, fine-tune, and evaluate deep learning algorithms for computer vision tasks (e.g., object detection, classification, segmentation, tracking).
- 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, Kubeflow, AWS SageMaker).

Your next step

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Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

 

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 or higher 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.
  • Mission Alignment: Work closely with mission partners, domain experts, and technical teams to understand real-world operational challenges and translate them into practical ML requirements.
  • MLOps & Pipeline Automation: Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring using modern tools (such as MLflow, Kubeflow, and GitLab CI/CD).
  • Model Development & Tuning: Train, fine-tune, and evaluate deep learning algorithms for computer vision tasks (e.g., object detection, classification, segmentation, tracking).
  • System Integration: Collaborate with cross-functional software engineers and cloud architects to integrate ML models cleanly into larger enterprise systems and secure 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, Kubeflow, AWS SageMaker).
  • 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 management. 

Physical Requirements

  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 10–15 pounds at times.

 

#JT

The pay range listed for this position reflects the wage or salary range NT Concepts expects to pay for this role at the time of posting. The compensation offered to a successful candidate within this range will be based on legitimate, job-related factors, including (but not limited to) the candidate's work location, education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements.

 

Virginia Pay Range
$120,336—$180,504 USD

About NT Concepts

Founded in 1998 and headquartered in the Washington DC Metro area, NT Concepts is a private, mid-tier company with clients spanning the Intelligence and Defense communities. We deliver end-to-end ​data and technology solutions ​that advance the modernization, transformation, and automation of the national security mission—solutions with real impact developed in a strong engineering culture that encourages technical growth, leadership, and creative “big idea” problem-solving.

Employees are the core of NT Concepts. We understand that world-changing concepts happen in collaborative environments. We are a company where talented teams work together using innovation and expertise to solve our clients’ most critical challenges. Here, you’ll gain competitive benefits, opportunities to bolster your skills and develop new abilities, and a company culture dedicated to support and service. In addition to our benefits program, we encourage our employees to take part in #NTC_GivesBack, which paves the way for positive social change.

If joining a stable company with strong professional growth opportunities resonates with you, and you seek vital, mission-driven projects (for some pretty cool clients) that use your specific talents, we’d love to have you move forward with us.

 

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Pay
Virginia Pay Range $120,336—$180,504 USD About NT Concepts
Location & working pattern

Chantilly, VA

Clearance: Active TS/SCI required (CI Polygraph or higher preferred or must be eligible to obtain) Location/Flexibility: Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available) Responsibilities
Work authorization

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