Performance Engineer

Hippocratic AI•Palo Alto, CA

About The Position

We're hiring a Performance Engineer to own performance across our entire stack. You'll build the automated harnesses that keep us honest, continuously measuring every model, microservice, and infrastructure component, and be our expert voice on VoIP quality characterization. This is a high-impact, highly technical role that cuts across ML infrastructure, backend services, and real-time communications.

Requirements

10+ years in performance engineering with a solid software development and SRE background
Proven track record building automated performance test harnesses (Locust, k6, Gatling, JMeter, or custom tooling)
Deep hands-on experience with PostgreSQL performance tuning (execution plans, indexing strategies, connection pooling, autovacuum) and Redis (eviction policies, clustering, pipelining)
Solid grasp of distributed systems fundamentals: queueing theory, tail latency, backpressure, cascading failures
Fluency with observability tools: Prometheus, Grafana, Cloudwatch, etc.
Working knowledge of SIP, RTP/RTCP, and RTCP-XR
Hands-on experience with VoIP testing tools (SIPp or equivalent) and interpreting call quality reports
Ability to diagnose audio degradation across network, codec, and application layers
Familiarity with MOS scoring methodologies (PESQ, POLQA, or E-model)

Nice To Haves

Experience benchmarking ML inference servers: vLLM, TensorRT-LLM, Triton, or similar
Kubernetes workload profiling and resource right-sizing
Chaos engineering experience: Toxiproxy, Gremlin, or Chaos Monkey
Background in healthcare tech, real-time communications, or other high-reliability, latency-sensitive systems

Responsibilities

Build Automated Performance Harnesses
Design and maintain automated performance testing frameworks covering the full system: LLM inference, REST/gRPC microservices, and infrastructure components including PostgreSQL, Redis, message queues, and object storage
Integrate performance suites into CI/CD so every deploy is gated against latency and throughput regressions
Define SLIs/SLOs and build dashboards (e.g., Grafana) that give engineering teams real-time visibility into system health
Characterize VoIP Performance
Measure and track VoIP quality metrics: MOS scores, jitter, packet loss, latency, echo, and codec fidelity
Build synthetic call load testing infrastructure to stress telephony paths at scale
Correlate audio degradation signals with underlying infrastructure metrics to root-cause issues
Drive a Performance Culture
Partner with ML, Speech, Backend, and Infra teams to turn performance findings into prioritized engineering work
Contribute to incident reviews where latency or audio quality was a factor
Write runbooks, share learnings, and help other engineers instrument their own services