Responsibilities
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.
Key ResponsibilitiesModel 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
Required Qualifications
- 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
Remote/hybrid status is subject to change based on Noblis and/or government requirements.
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 $90,700.00 - USD $251,325.00 /Yr.
