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# AI/ML Engineer, Mid (Clearance Required)

- **Company:** Noblis Inc.
- **Location:** Reston, VA, United States
- **Experience:** Experienced
- **Salary:** $207,750.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), A/B Testing, Artificial Intelligence, Amazon Web Services, Big Data, Software Quality, Continuous Integration, DevOps, Distributed Systems, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Cloud Services, Tensorflow, Azure Machine Learning, Software Engineering, Reinforcement Learning, Feature Engineering, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Deep Learning, Model Validation, Generative AI, Backend, Fastapi, Containerization, Scikit Learn, Kubernetes, Dask, Machine Learning Operations, Front End Software Development, Docker
- **Published:** July 13, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9027135/aiml-engineer-mid-clearance-required

## About the Role

* Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph.
 * Bachelor's degree with 5 years of related experience; OR Master's degree with 3 years of related experience; OR associate's degree with 8 years of related experience; OR High School diploma/GED with 11 years of related experience.
 * Experience deploying machine learning (ML) models to production, including large language models (LLMs)
 * Strong proficiency 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, including CI/CD, model deployment, monitoring, and automation
 * U.S. Citizenship is required, * Expert-level proficiency in Python with extensive experience across leading machine learning (ML) frameworks, including TensorFlow, PyTorch, and scikit-learn
 * Proven ability to design and implement end-to-end machine learning (ML) pipelines, spanning data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
 * Extensive experience with large language models (LLMs), including fine-tuning, prompt engineering, retrieval-augmented generation (RAG), agentic workflows, and responsible AI practices
 * Expertise in advanced machine learning (ML) techniques, including deep learning, reinforcement learning, generative models, ensemble methods, and modern model optimization approaches
 * Proven track record of designing and implementing production-grade MLOps infrastructure, including automated model retraining, monitoring, drift detection, and CI/CD pipelines using tools such as MLflow, Kubeflow, and SageMaker Pipelines
 * Hands-on experience architecting and deploying scalable machine learning (ML) solutions on cloud platforms (e.g., AWS SageMaker, Azure Machine Learning, Google Vertex AI) with a focus on scalability, reliability, and cost optimization
 * Demonstrated experience leading technical architecture decisions and mentoring engineers on machine learning (ML) best practices, software engineering standards, experimentation, code quality, and research methodology
 * Strong background in distributed computing and big data technologies such as Apache Spark, Ray, and Dask for efficient model training and inference
 * Proficiency with containerization and orchestration technologies, including Docker and Kubernetes, to support scalable model serving, A/B testing, and canary releases/deployments.
 * Demonstrated ability to translate complex business problems into well-scoped ML solutions, communicating trade-offs, risks, and ROI to executive stakeholders
 * Experience contributing to or publishing applied ML research, patents, conference presentations, or open-source projects
 * 7+ years of experience designing, developing, and deploying machine learning systems at scale in production environments

## Description

Noblis is seeking an experienced AI/ML Engineer to support mission-critical national security initiatives., * 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 sc ale 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 adopt state-of-the-art AI/ML models, frameworks, and emerging technologies.
 + Architect scalable and resilient infrastructure to support evolving AI/ML workloads and mission requirements.
 + Establish and promote best practices for production-grade machine learning (ML) systems, including security, observability, and governance.
 + Provide technical guidance and thought leadership across AI/ML initiatives and engineering teams.


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