AI/ML Engineer (Clearance Required)

Noblis Inc.
Reston, VA, United States
29 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time / full-time
Experience level
Expert
Experience required
9 years minimum
Compensation
$171,525.0
Working hours
Regular working hours

Tech stack

JavaScript (Programming Language) Artificial Intelligence Amazon Web Services Big Data Continuous Integration Data Cleansing DevOps Distributed Computing Environment Monitoring of Systems Python (Programming Language) Machine Learning Cloud Services
+20 more
Tensorflow Azure Machine Learning Software Deployment Data Processing Feature Engineering Pytorch Large Language Models Apache Spark Deep Learning Model Validation Backend Fastapi Containerization Scikit Learn Kubernetes Dask Machine Learning Operations Front End Software Development Software Version Control Docker

Job description

Noblis is seeking an AI/ML Engineer with a TS/SCI with Polygraph to support mission-critical national security initiatives.

In this role, you will design, develop, and deploy advanced machine learning and AI solutions while building the scalable infrastructure needed to operationalize AI capabilities in secure, production environments.

Job Responsibilities:

  • Model Development & Deployment
  • Design, develop, and containerize machine learning (ML) models using modern frameworks and tools, including PyTorch, Ray, Docker, and FastAPI.
  • Deploy, manage, and scale production ML workloads on Kubernetes.
  • Integrate AI/ML capabilities into full-stack applications using Python-based backend services and JavaScript frontend technologies.
  • Ensure model reliability, performance, and maintainability throughout the deployment lifecycle.

  • Infrastructure & Operations
  • Architect and implement cloud-native ML infrastructure on AWS.
  • Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment, and monitoring.
  • Deploy and support AI/ML systems within secure, classified, and high side environments.

  • Technical Leadership
  • Evaluate and integrate state-of-the-art AI/ML models, frameworks, and emerging technologies to enhance mission capabilities and accelerate innovation
  • Architect scalable, resilient, and secure infrastructure to support evolving AI/ML workloads, production deployments, and mission-critical requirements
  • Establish and champion best practices for production-grade machine learning (ML) systems, including MLOps, security, observability, governance.
  • Provide technical guidance across AI/ML initiatives and engineering teams.

Requirements

  • Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph
  • Bachelor’s degree with 3 years of related experience; OR Master’s degree with 1 years of related experience; OR associate’s degree with 6 years of related experience; OR High School diploma/GED with 9 years of related experience
  • Demonstrated experience deploying machine learning (ML) models to production, including large language models (LLMs)
  • Demonstrated experience with machine learning (ML) frameworks and containerization technologies (e.g., PyTorch, Docker, and Kubernetes)
  • Full-stack software development experience using Python and JavaScript
  • Working knowledge of AWS cloud services and infrastructure
  • Demonstrated experience implementing MLOps and DevOps best practices
  • U.S. Citizenship is required, * Proficiency in Python with hands-on experience using leading machine learning frameworks, including TensorFlow, PyTorch, or scikit-learn
  • Experience designing and implementing end-to-end machine learning (ML) pipelines, including data preprocessing, feature engineering
  • Familiarity with cloud-based machine learning (ML) platforms such as AWS SageMaker, Azure Machine Learning, or Google Vertex AI
  • Understanding of MLOps best practices, including model versioning, experiment tracking, model monitoring, and CI/CD for machine learning (ML) workflows using tools such as MLflow, Weights & Biases, or DVC
  • Ability to collaborate with cross-functional teams including data engineers, product managers, and domain experts to translate business problems into ML solutions
  • Experience working with large-scale datasets and distributed computing frameworks such as Apache Spark or Dask to support efficient data processing and model training
  • Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) for scalable model serving and orchestration
  • Strong communication skills with the ability to explain model behavior, trade-offs, and results to both technical and non-technical stakeholders

Benefits & conditions

If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact us .

EEO is the Law E-Verify Right to Work

Total Rewards

At Noblis we recognize and reward your contributions, provide you with growth opportunities, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, and work-life programs. Our award programs acknowledge employees for exceptional performance and superior demonstration of our service standards. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in our benefit programs. Other offerings may be provided for employees not within this category. We encourage you to learn more about our total benefits by visiting the Benefits page on our Careers site.

Compensation at Noblis is determined by various factors, including but not limited to, the combination of education, certifications, knowledge, skills, competencies, and experience, internal and external equity, location, clearance level, as well as contract-specific affordability, organizational requirements and applicable employment laws. The projected compensation range for this position is based on full time status. For part time or on-call staff, compensation is proportionately adjusted based on hours worked. While monetary compensation is important, it’s just one component of Noblis’ total compensation package.

Posted Salary Range

USD $109,800.00 - USD $171,525.00 /Yr.

About the company

Noblis and our wholly owned subsidiaries, Noblis ESI and Noblis MSD, take on some of the nation’s toughest challenges, delivering advanced solutions to our customers’ most critical missions. We bring together leading scientific, engineering, and management expertise in a culture grounded in objectivity and collaboration, ensuring our work creates lasting impact across federal missions.

We work with a broad range of government agencies in the defense, intelligence, and federal civilian sectors. Learn more and find opportunities at careers.noblis.org

Why Work at Noblis

At Noblis, we share a passion for excellence and innovation, and we create an environment where people can do meaningful work while maintaining the balance that keeps them energized and fulfilled. We seek out individuals with a natural curiosity and desire to collaborate and learn. We believe our people are our greatest strength, and we consistently seek exceptionally skilled, mission-driven professionals who care deeply about doing work that enriches lives and makes our nation safer.

Noblis has earned numerous workplace awards for our culture, our commitment to employee well-being, and our dedication to meaningful, impactful work. We also maintain a drug-free workplace.

Remote/hybrid status is subject to change based on Noblis and/or government requirements.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.clearancejobs.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · WWC Europe 2026

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

2:19 min

Scaling performance across multiple GPUs using specialized frameworks

Paul Graham Paul Graham · WWC 2025

2:12 min

Navigating technical clarity as a global black belt

Chris Heilmann +2 · LIVE

3:18 min

Scaling global network engineering through DevOps culture

Stuart Clark · LIVE

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · WWC Europe 2026

Videos

See all

Related articles

See all