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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - Multiple levels (Cleared) - **Company:** Noblis Inc. - **Location:** Reston, VA, United States - **Experience:** Starter - **Salary:** $90,700.0 - $171,525.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), A/B Testing, Artificial Intelligence, Amazon Web Services, Big Data, Software Quality, DevOps, Distributed Systems, Design of User Interfaces, Human-Computer Interaction, Python (Programming Language), Machine Learning, Performance Tuning, Systems Development Life Cycle, Tensorflow, Azure Machine Learning, Software Deployment, Software Engineering, Reinforcement Learning, Scripting, Feature Engineering, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Google Vertex AI, Deep Learning, Generative AI, Backend, Agentic-AI, Fastapi, Scikit Learn, Kubernetes, Dask, Machine Learning Operations, Drift Detection, Docker - **Published:** November 3, 2026 - **Apply:** https://www.careerbuilder.com/job-details/ai-ml-engineer-multiple-levels-cleared-reston-va--47f75ba6-1a7a-4ea2-9e3f-326c5b4ed848 ## About the Role Artificial Intelligence (AI), Top Secret Clearance, Sensitive Compartmented Information (SCI), Artificial Intelligence (AI), Machine Learning, Production Systems, Scalable System Development, Docker, Python Programming/Scripting Language, User Interface/Experience (UI/UX), * Active Top Secret/SCI (TS/SCI) with Polygraph * S. Citizenship is required * Travel up to 10% within US. * Lift up to 30 lbs, walk, bend, drive. Junior level * Bachelor's, Master's, or PhD degree with 0-3 years of related experience including exposure or coursework in machine learning concepts and frameworks; OR Associate's degree with 3 years of related experience; OR High School diploma/GED with 6 years of related experience * Knowledge of machine learning frameworks and deploying ML models to production * Compensation: $90,700 - $171,525 Mid-level * 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 with machine learning frameworks and deploying ML models to production * Compensation: $132,900 - $207,750 Senior level * Bachelor's degree with 8 years of related experience; OR Master's degree with 6 years of related experience; OR Associate's degree with 11 years of related experience; OR High School diploma/GED with 14 years of related experience * Experience with machine learning frameworks and deploying ML models to production * Compensation: $160,800 - $251,325 Desired Qualifications: * Full-stack software development experience using Python and JavaScript * 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 ## Description Noblis is seeking AI/ML Engineers at all experience levels with an active TS/SCI with a 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., 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, and governance * Provide technical guidance and thought leadership across AI/ML initiatives and engineering teams