Position Overview
As an AI Systems & Solutions Engineer, you will support enterprise-level digital engineering, manufacturing modernization, and operations analytics initiatives across the Oak Ridge Enrichment Operations site. You will develop open-source AI tools, maintain production AI stacks, and design ML-driven solutions that support digital thread integration, operational optimization, and engineering decision-making. This role interacts with engineering, manufacturing, operations, and automation teams to deliver reliable, scalable, and secure AI capabilities for high-value missions.

Location
On-site in Oak Ridge, Tennessee

Your Day to Day as an AI Systems & Solutions Engineer
• Architect and maintain open-source AI/ML tools, including model training and inference pipelines.
• Build and support full AI stacks using Python, MLflow, TensorFlow/PyTorch, Docker, Git, and Kubernetes.
• Design AI/ML solutions for manufacturing optimization, engineering workflows, business informatics, and IoT monitoring.
• Integrate AI systems with digital thread/twin environments, PLM/CAD, MES/SCADA, and enterprise data platforms.
• Develop APIs and microservices for model orchestration and data ingestion.
• Implement CI/CD workflows for AI workloads.
• Build end-to-end pipelines for sensor, IoT, and streaming data, including anomaly detection and predictive maintenance.
• Collaborate with engineering and operations teams to shape deployable AI solutions.
• Produce documentation, model explainability summaries, and technical reports.
• Mentor junior engineers on AI/ML development.

Required Qualifications
• B.S. or M.S. in Computer Science, Engineering, Data Science, or related field.
• 5+ years developing AI/ML pipelines with open-source tools.
• Experience operating AI stacks in production environments with Git, Docker, Kubernetes, CI/CD.
• Background in manufacturing, engineering, business informatics, or IoT analytics.
• Experience building API/microservice-based ML applications.
• Strong ability to structure AI solutions around complex operational challenges.
• Excellent cross-team communication and documentation skills.
• Must be a U.S. citizen with ability to obtain and maintain DOE clearance.

Preferred Qualifications
• Experience with digital thread/twin, PLM/CAD, MES/SCADA, or industrial IoT.
• Familiarity with MLOps tools such as MLflow, Kubeflow, Prefect, Dagster, or Argo.
• Knowledge of Kafka, Spark, Airflow, or Delta Lake.
• Experience with advanced ML methods (CV, NLP, RL, anomaly detection).
• Experience deploying AI in regulated or high-security environments.
• Contributions to open-source projects.

What We Offer
• Competitive salary and benefits.
• Flexible work schedules and paid time off (as applicable).
• Professional development and mentorship.
• Inclusive culture that values diverse perspectives.
• Work that directly supports national security missions.
• Continuous learning and career-growth opportunities.

Pay: $$86,450 $123,500 $160,550 - $86,450

The base salary range for this position in Tennessee (US-TN) at the start of employment is expected to be between $$86,450 $123,500 $160,550 and $86,450 per year. However, the base salary offered is based on local job market factors, and may vary further depending on factors specific to the selected job candidate, such as job-related knowledge, skills, experience, and other objective business considerations. Subject to these considerations, the total compensation package for this position may also include other elements, such as an annual cash incentive in addition to a full range of medical, retirement, and/or other benefits. Details of participation in these benefit plans will be provided at such time the selected job candidate receives an offer of employment. If hired, the selected job candidate will be employed 'at-will,' unless employed at a location and in a position subject to a collective bargaining agreement. The company further reserves the right to modify base salary (as well as any other discretionary payment, compensation or benefit program) at any time, including for reasons related to individual performance, company or individual department/team performance, and other market factors.