Artificial Intelligence/Machine Learning SME
Scientific Research Corporation6 months ago
Augusta, GA, USAStaff+
Responsibilities
- Serve as the primary AI/ML Engineering subject matter expert for AIDETL interns and staff.
- Provide guidance on AI strategy, architecture, policy, implementation, and best practices.
- Deliver expert-level AI/ML training, workshops, and briefings and assist with curriculum development.
- Build and maintain data pipelines, feature pipelines, model-training workflows, and production model-serving systems.
- Train and tune algorithms, including deep-learning models, to improve predictive accuracy and decision-support capabilities.
- Build end-to-end MLOps pipelines with model versioning, monitoring, automated testing, model validation, drift detection, data-quality checks, and audit trails.
- Deploy and operate models in development and production environments while ensuring reliability, performance, scalability, and compliance.
- Identify and integrate commercial off-the-shelf, government, and custom tools within established frameworks.
- Collaborate with cross-functional teams to align solutions with enterprise architecture, cybersecurity, and security requirements.
- Analyze system performance metrics and recommend improvements in efficiency and scalability.
- Mentor interns and junior engineers, lead cross-functional AI projects, and communicate technical concepts to technical and non-technical audiences.
Requirements
- Secret clearance and U.S. citizenship are required.
- A bachelor's degree in computer science, data science, artificial intelligence, engineering, or a related technical discipline plus 12–15 years of relevant experience, or a related master's degree plus 10–13 years of relevant experience.
- At least 5 years designing, building, and operating end-to-end AI/ML infrastructure in production environments.
- Expert-level proficiency with at least two of TensorFlow, PyTorch, JAX, or Scikit-Learn, including deep-learning architectures such as CNNs, RNNs, and Transformers and explainability methods such as SHAP, LIME, and counterfactuals.
- Experience building MLOps pipelines and deploying models using tools such as Kubeflow, MLflow, or TFX or similar technologies.
- Experience with pipeline instrumentation, monitoring, model-drift detection, data-quality checks, and compliance or audit trails.
- Strong programming skills in Python, R, or Java.
- Experience translating business problems such as computer vision, NLP, predictive maintenance, and anomaly detection into production ML solutions and evaluating them against domain-specific KPIs.
- Hands-on experience with generative AI, prompt engineering, chain-of-thought reasoning, and NLP tasks including entity extraction, summarization, and semantic search.
- Experience mentoring junior engineers, leading cross-functional AI projects, and presenting technical concepts to executives, product owners, and compliance teams.
- Familiarity with virtualized and containerized deployment environments such as VMware, Docker, and Kubernetes.
- Strong project management, documentation, presentation, communication, problem-solving, and analytical skills.
- Preferred qualifications include 12 or more years in AI/ML or data engineering, Agile Scrum team leadership, multi-enclave DoD experience, automated model validation and bias detection, enterprise API and microservices integration, GPU optimization, enterprise analytics or AI modernization, relevant publications or open-source contributions, AI-agent evaluation and observability, AI service integration, GPU programming, LLMs, and agent frameworks.
Benefits
- Medical, dental, and vision insurance plans.
- 401(k) with company match, life insurance, vacation and sick paid time off accruals, and 11 paid holidays.
- Tuition reimbursement and a work environment that encourages excellence.
- Approximately 10% travel, primarily to academic institutions and also to cyber and physical ranges or industry events.
- Position filling is contingent upon funding.
Tech Stack
Categories
About Scientific Research Corporation
Scientific Research Corporation is a privately held engineering services and systems integration firm that builds and sustains communications, C4ISR, electronic warfare, radar, and simulation/instrumentation systems for U.S. defense and government customers and international markets. Founded in 1988 and headquartered in Atlanta, it delivers design, integration, test, and lifecycle support under contract, with engineering offices across the United States.