Artificial Intelligence​/Machine Learning SME

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 will include, but may not be limited to:

• 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

filling this position is contingent upon funding

#li-hk1

• 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: tensor flow, 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, cloud watch/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…