LLM Inference Engineer (Mid, Sr, Staff)

What you will accomplish

Own your first major outcome: By day 90, you will have shipped a measurable improvement to our inference serving stack (reduced latency, improved throughput, or optimized cost per inference), validated the gains across our production deployment scenarios, and established the performance optimization roadmap that will guide infrastructure investment.

Drive lasting impact: At 12 months, you will have designed and deployed advanced serving architectures (disaggregated inference, optimized caching, speculative decoding) that meaningfully improve patient experience and operational efficiency, contributed novel optimization techniques that become part of our core infrastructure, and made our serving stack a durable competitive advantage in healthcare AI deployment.

What you'll do

• Design and implement multi-node serving architectures for distributed LLM inference
• Optimize multi-LoRA serving systems
• Apply advanced quantization techniques (FP4/FP6) to reduce model footprint while preserving quality