AI/ML Inference Systems Engineer — Scale & Latency

Energy Jobline ZR; Los Angeles (CA); Presencial; USD 204.000 - 216.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Generous health & wellness benefits

Descripción de la vacante

Sapience AI is seeking an experienced ML Infrastructure Engineer to own and scale the inference infrastructure for MINERVA and COGENT. You will ensure fast, reliable model serving at production scale across communities, with a focus on latency, cost efficiency, and operational excellence.

You will work closely with Applied AI, Platform Engineering, and Research to ship safe, production-ready inference capabilities. This role emphasizes reliability, observability, and scalable cloud-based systems.

Formación

• Five or more years in infrastructure, systems, or ML infrastructure engineering.
• Hands-on experience serving ML or LLM models in production at scale.
• Deep understanding of latency, throughput, and performance optimization.
• Experience with GPUs or accelerators and their efficient use.
• Strong systems programming and distributed systems fundamentals.
• A track record of reliable, cost-aware production systems.
• Fluency with observability and operational excellence.

Responsabilidades

• 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.

Conocimientos

Inference serving

Distributed systems

Latency optimization

GPU acceleration

Go/Rust/C++

Herramientas

vLLM/Triton

Kubernetes

CUDA tools

Python

Descripción del empleo

Sapience AI is seeking an experienced ML Infrastructure Engineer to own and scale the inference infrastructure for MINERVA and COGENT. You will ensure fast, reliable model serving at production scale across communities, with a focus on latency, cost efficiency, and operational excellence.

You will work closely with Applied AI, Platform Engineering, and Research to ship safe, production-ready inference capabilities. This role emphasizes reliability, observability, and scalable cloud-based systems.