Member of Technical Staff

Simplify; San Francisco (CA); On-site; USD 200,000 - 300,000; Full time

Benefits offered by this job

Housing stipend

Uber/Waymo rides

Job summary

Simplify in San Francisco is hiring Members of Technical Staff to build systems that accelerate LLM inference and own customer workloads end to end. You will work on high-performance kernels, inference engine internals, and production infrastructure for named accounts.

You will own client relationships, be on-site in SF five days a week, and help drive technical evaluations with real workloads while collaborating with a fast-growing AI inference company.

Qualifications

• Shipped and operated production systems; on-call experience.
• Had a customer relationship or a deployment with real users.
• Credible in a room full of engineers; can defend a benchmark methodology.
• Able to work without a spec.
• In person in San Francisco, 5 days/week.
• Already in the US (they sponsor and transfer essentially any visa status).

Responsibilities

• Develop and optimize high-performance computing kernels and work across inference engine internals and serving infrastructure.
• Develop AI agents to do autonomous inference engineering.
• Design, deploy, and operate heterogeneous clusters across vendors.
• Own customer accounts end to end and maintain production for workloads.
• Explain benchmark results to customers' engineers and drive technical evaluations.
• Inform product roadmap with real-load observations from accounts.

Skills

Production systems

On-call debugging

Customer relationship

Benchmark methodology

In-person SF

Job description

Most job posts are designed to collect as many applications as possible.

This is not one of them.

At Simplify, we work directly with startup founders to help them hire for high-priority roles.

We're partnering with a fast-growing AI inference company in San Francisco to hire Members of Technical Staff — engineers who build the systems that make LLM inference fast, and own the customers running on them. $200–300K base + equity, and they're hiring multiple engineers now.

About the company

One-liner: Building the infrastructure that makes LLM inference fast — and putting the engineers who build it directly in front of the customers who run on it

Stage: Small team, HQ in SF. Their customers include Vercel and Neon Health, and the engineers own those relationships directly — no solutions team, no layer between you and the workload.

Most infra engineers ship into a backlog and never meet the people running their code. Here, sales gets the first meeting — from there, you decide what to prove, build it, win the technical evaluation on the customer's own workload, and keep it running in production. Each engineer owns 3–4 named accounts outright.

What you'll work on

• Develop and optimize high-performance computing kernels, and work across inference engine internals and serving infrastructure
• Develop AI agents to do autonomous inference engineering
• Design, deploy, and operate heterogeneous clusters across vendors
• Own customer accounts end to end. Sales gets the first meeting. From there you decide what to prove, you build it, you keep it running in production, and you carry the relationship
• Win the technical evaluation. Prove Wafer on the customer's own workload rather than a synthetic benchmark, and be the person who can explain the result to their engineers
• Own production for your accounts. When latency moves or error rates climb, you find it, you fix it or route it, and you are who the customer hears from
• Inform product roadmap. You sit closer than anyone to how Wafer behaves under real load, and the engineering team builds against what you report

What we look for

• You've shipped and operated production systems — been on call, personally debugged production problems, and can walk through how you found them
• You've owned a customer relationship or a deployment with real users — you can name it, and you were the person people came to
• Credible in a room full of engineers — you can defend a benchmark methodology
• Able to work without a spec
• In person in San Francisco, 5 days/week
• Already in the US (they sponsor and transfer essentially any visa status — H-1B, O-1, TN, STEM OPT)

Nice to have

• Inference / model serving experience (vLLM, SGLang, TensorRT-LLM, Triton) — their most useful differentiator, but they'll interview a strong engineer without it
• Early-stage or founding experience — if you've sold your own product to engineers, you've already done both halves of this job
• Heavy use of AI agents and tooling in your own workflow
• $200–300K base + equity — plus a $1K/month housing stipend near the office and covered Uber/Waymo rides
• No years-of-experience requirement in either direction — the bar is what you've operated, not how long you've worked
• Your work shows up directly in customer production systems, and you carry the relationship
• Small fast-moving team, high ownership — you own named accounts outright from day one
• They're moving fast: offers signed by end of August