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.
Chantilly, VA
Live, first seen by us 60 days agoVirginia Pay Range $120,336—$180,504 USD About NT ConceptsRead the full posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Clearance: Active TS/SCI clearance
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
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
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.
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
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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.
Day 60
Similar jobs usually come down between day 6 and day 70.
From 4,504 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
- 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).
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Already applied? Track this application
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
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.
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.
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.
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
Qualifications
Preferred / Desired Skills:
Physical Requirements
#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.
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Virginia Pay Range $120,336—$180,504 USD About NT Concepts
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
No clear work-authorization passage found. Eligibility is unconfirmed.