Performance Engineer
Job in
Menlo Park, San Mateo County, California, 94029, USA
Listed on 2026-06-10
Listing for:
Hippocratic AI
Full Time
position Listed on 2026-06-10
Job specializations:
-
Engineering
Systems Engineer, AI Engineer (Applied/Software), Software Engineer
Job Description & How to Apply Below
Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs as part of our Polaris constellation, resulting in a system with over 99.9% accuracy.
Why Join Our Team
Reinvent healthcare with AI that puts safety first. We're building the world's first healthcare-only, safety-focused LLM - a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation.
Work with the people shaping the future. Hippocratic AI was co-founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA.
Backed by the world's leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from Capital
G, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children's, Well Span Health, John Doerr, Rick Klausner, and others.
Build alongside the best in healthcare and AI. Join experts who've spent their careers improving care, advancing science, and building world-changing technologies - ensuring our platform is powerful, trusted, and truly transformative.
About the Role
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.
What You'll Do
Build Automated Performance Harnesses
- Design and maintain automated performance testing frameworks covering the full system: LLM inference, REST/gRPC microservices, and infrastructure components including Postgre
SQL, 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
- 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
- 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
Must-Have:
- BS in Computer Science or equivalent
- 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 Postgre
SQL 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, back pressure, 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)
- Experience benchmarking ML inference servers: vLLM, Tensor
RT-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
Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from email addresses. We will never request payment or sensitive personal information during the hiring process.
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