Artificial Intelligence/Machine Learning SME at Scientific Research Corporation in US-GA-Augusta

Job description

• Scientific Research Corporation (SRC) is seeking a highly experienced Subject Matter Expert (SME) in AI/ML Engineering to support the Test Resource Management Center’s operation of the Artificial Intelligence Digital Engineering Test Laboratory (AIDETL) in Augusta, Georgia. This role will be pivotal in developing the next generation of government AI Test & Evaluation professionals for the Department of War.
• In this role, you will work alongside other SME’s, students, interns, engineers, AI and DE experts from academia and other industry teammates to translate operational and strategic requirements into educational opportunities as well as scalable, production-ready solutions. You will contribute directly to product planning, execution, intern mentoring and continuous improvement—helping ensure qualified individuals are delivered efficiently to the Department of War and positioned for sustained success.
• This position offers the opportunity to work on a high-visibility, mentorship program at the intersection of data, analytics, and emerging AI technologies. Ideal candidates are motivated by mission impact, have strong interpersonal skills and the willingness to mentor interns, must be comfortable operating in complex stakeholder environments, and interested in building deep domain expertise while delivering capabilities and training individuals with real-world national security outcomes.

Responsibilities

• Serving as the primary Subject Matter Expert on AI/ML Engineering for the AIDETL Interns and staff, providing authoritative guidance on AI strategy, architecture, policy, and implementation aligned with the AIDETL’s mission objectives
• Providing expert-level training, workshops, and briefings to AIDETL Interns on AI/ML concepts and AI/ML best practices
• Assisting in AIDETL curriculum development
• Building and maintaining data pipelines for efficient data processing and model training
• Training and tuning algorithms to improve predictive accuracy and decision-support tasks
• Deploying models into production environments, ensuring reliability and performance
• Identifying and integrating appropriate COTS, government, and custom tools within established frameworks
• Collaborating with cross-functional teams to ensure alignment with enterprise architecture and security requirements
• Staying updated on industry trends and advancements in AI/ML technologies
• Developing and implementing best practices for model development and deployment
• Ensuring compliance with cybersecurity policies and standards throughout the project lifecycle
• Analyzing system performance metrics and recommend improvements for efficiency and scalability

Requirements

• Secret clearance
• Bachelor’s degree in computer science, Data Science, Artificial Intelligence, Engineering, or related technical discipline and 12–15 years of relevant experience OR Master’s degree in a related field and 10–13 years of relevant experience.
• 5 + years designing, building, and operating end‑to‑end AI/ML infrastructure (data ingestion, feature pipelines, model training, and serving) in production environments.
• Expert‑level proficiency with at least two of the following: TensorFlow, PyTorch, JAX, or Scikit‑Learn, including design of deep‑learning architectures (CNN, RNN, Transformer) and model‑explainability methods (SHAP, LIME, Counterfactuals).
• Proven ability to build end‑to‑end MLOps pipelines (CI/CD, automated testing, model versioning, monitoring) using Kubeflow, MLflow, TFX, or similar tools, and to deploy models in production and development environments.
• Experience instrumenting pipelines with Prometheus, Grafana, CloudWatch/Stackdriver, Open Telemetry; implementing automated model‑drift detection, data‑quality checks, and compliance/audit trails.
• Ability to translate complex business problems (e.g., computer vision, NLP, predictive maintenance, anomaly detection) into robust ML solutions and evaluate them against domain‑specific KPIs (accuracy, latency, cost, safety).
• Strong programming skills in languages such as Python, R, or Java.
• Strong problem-solving abilities and analytical thinking.
• Strong communication and interpersonal skills.
• Solid understanding and hands-on experience with generative AI models including prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search.
• Experience mentoring junior engineers, leading cross‑functional AI projects, and clearly communicating technical concepts to both technical and non‑technical audiences (executives, product owners, compliance teams).
• Excellent documentation and presentation skills are required Familiarity with deployment into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes).
• Strong project management skills with the ability to own initiative execution from start to finish, adapting to evolving AIDETL curriculum needs and mission priorities.
• 12+ years of experience in AI/ML and/or data engineering or related fields.
• Experience leading and managing Agile SCRUM teams. (Strong familiarity with Agile Scrum processes and methodologies)
• Experience supporting AI/ML solutions across multi-enclave DoD environments.
• Experience implementing automated model validation, bias detection, and drift monitoring frameworks.
• Experience integrating AI services into enterprise APIs and microservices architectures.
• Experience optimizing GPU-based training and inference pipelines.
• Experience supporting enterprise-scale analytics, data platforms, or AI modernization initiatives.
• Publications, patents, or open ‑ source contributions that demonstrate thought ‑ leadership in emerging AI areas such as foundation models, reinforcement learning, federated learning, or privacy ‑ preserving ML.
• Familiarity with evaluation and observability tools for AI agents, such as LangSmith, OpenAI Evals, or custom telemetry systems.
• Experience with AI service integration such as NIMS, Azure OpenAI, Bedrock, GCP Vertex AI.
• Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow, including optimization for performance and efficiency.
• Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen.

Skills

Required

• TensorFlow
• PyTorch
• JAX
• Scikit‑Learn
• Kubeflow
• MLflow
• TFX
• Prometheus
• Grafana
• CloudWatch/Stackdriver
• Open Telemetry
• Python

Preferred

• Agile SCRUM
• LangSmith
• OpenAI Evals
• NIMS
• Azure OpenAI
• Bedrock
• GCP Vertex AI
• CUDA