AI/ML Infra / Systems Engineer (Inference)

Sapience AI is a collective intelligence platform for professional communities that connects expertise across CRMs, association management systems, and knowledge bases. The AI/ML Infrastructure and Systems Engineer will build and operate inference infrastructure for the MINERVA and COGENT systems, focusing on serving, performance, scalability, reliability, cost efficiency, deployment, observability, and hardware choices.

Responsibilities:

• Build and operate the inference systems that serve models and reasoning behind MINERVA and COGENT
• Own the serving path end to end, from request to response, under real load
• Make serving robust to failure, traffic spikes, and change
• Drive down latency so members get fast answers, and keep it low as the platform grows
• Optimize the full path, including model execution, batching, caching, and retrieval
• Profile relentlessly and remove the bottlenecks that matter
• Scale inference to more members, more communities, and heavier reasoning without losing reliability
• Build autoscaling, load management, and graceful degradation
• Own the reliability of the serving layer as a first-order responsibility
• Own the economics of inference, including GPU and hardware efficiency at scale
• Improve utilization and cut waste without hurting quality or speed
• Make cost a designed property, not a surprise
• Build the paths that take models and reasoning components from research to production safely
• Support rollout, versioning, and rollback with confidence
• Give applied AI and research a fast, safe route to ship
• Instrument the serving layer so it can be measured, debugged, and trusted
• Build the alerts, dashboards, and tooling that keep inference healthy
• Reduce the operational burden of running AI at scale
• Make sound choices about accelerators, runtimes, and serving frameworks
• Balance performance, cost, and maintainability in platform decisions
• Keep the stack current as inference technology moves