AI​/ML and Data Engineer

Description

Responsible for providing both strategic and hands‑on technical leadership for SME's AI/ML, Generative AI, and modern data platforms, advancing SME's nonprofit mission to accelerate adoption of manufacturing technology and strengthen the manufacturing talent pipeline. The incumbent designs, builds, and deploys practical AI capabilities and governed data systems that enable SME insights, products, and services—including workforce development initiatives—while serving as an advisor under the direction of the Director to internal leaders, members, partners, and manufacturers.

A critical component of this role is end‑to‑end delivery: translating manufacturing‑focused opportunities into secure, production‑grade AI solutions (including traditional ML and LLM‑enabled applications), building the underlying data foundation to support analytics and decision‑making, and providing client‑facing consulting services that demonstrate measurable value and responsible use of AI.

The position also contributes to organizational capability‑building by coaching stakeholders on appropriate AI use, shaping standards‑aligned governance practices, and representing SME's point of view on AI and data in manufacturing through partner engagement and industry thought leadership.

• Lead the design, development, and deployment of manufacturing‑focused AI solutions, including predictive maintenance, anomaly detection, process optimization, and related applied machine learning use cases.
• Architect and deliver LLM‑enabled Generative AI solutions (e.g., Retrieval‑Augmented Generation, tool use, and agentic workflows) that enable natural‑language access to SME knowledge assets such as research content, standards‑related material, membership and event data, and learning resources.
• Build and maintain a modern, scalable data platform that ingests, curates, and governs structured and unstructured manufacturing‑related datasets, ensuring data quality, metadata management, lineage, and appropriate access controls.
• Design and implement database patterns (relational, lakehouse, and vector databases) to support analytics, AI development, and reliable retrieval across SME content and partner datasets.
• Establish and mature MLOps/LLMOps practices, including CI/CD, model and prompt versioning, monitoring/observability, rollback procedures, and cost/performance optimization for production environments.
• Define evaluation approaches and quality controls for AI systems, including performance metrics, monitoring for drift, and iterative improvement loops that maintain reliability and trust over time.
• Oversee analytics engineering (ETL/ELT) supporting dashboards and reporting that inform SME decision‑making on industry trends, program outcomes, member engagement, and organizational performance.
• Conduct discovery workshops with manufacturers, members, and partners to identify priority AI/data opportunities, frame ROI and feasibility, and develop actionable implementation roadmaps.
• Lead pilot and proof‑of‑value engagements from requirements through deployment and knowledge transfer, ensuring solutions are supportable, secure, and aligned with stakeholder needs.
• Provide executive‑level advisory services on AI adoption and data modernization, tailoring recommendations for both technical and non‑technical stakeholders and enabling informed decision‑making.
• Author proposals, statements of work, technical approaches, and executive readouts that communicate scope, risks, outcomes, and measurable impact of AI/data initiatives.
• Implement and champion AI/data governance and security practices aligned with relevant frameworks, including privacy safeguards, auditability, and responsible AI principles (bias mitigation, explainability, and safe use guidance).
• Partner with internal stakeholders (e.g., workforce development, membership, research, standards‑related groups, events, and marketing) to ensure AI/data initiatives align with SME priorities and deliver clear value to the manufacturing community.
• Mentor team members and/or contractors in AI/data delivery best practices to improve consistency and execution quality.
• Serve as an internal subject…