Member of Technical Staff, Forward Deployed Engineer
Inferact
San Francisco, CA · $200k–$400k a year · Posted October 2, 2026
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Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing pays about $300,000 a year. Across 130 open member of technical staff listings that state pay, the middle half runs $208,000 to $270,000 and the median is $240,000. That is 25% above the median, above the middle half of those listings.
Listed pay is what employers advertise, not what people are paid.
Member of Technical Staff salaries by state · Check your own pay
How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
OVERVIEW
Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.
ABOUT THE ROLE
We're looking for a Forward Deployed Engineer to make Inferact successful inside real customer environments. You'll work directly with customers to deploy, integrate, debug, and optimize vLLM-powered inference systems across cloud, Kubernetes, GPU, networking, and model-serving environments.
This is a hands-on engineering role, not a traditional pre-sales position. You'll move from architecture discussions to implementation, own difficult production problems end-to-end, and work closely with core product and engineering teams to turn what you learn in the field into reusable product capabilities. Your work will directly affect customer time-to-value and how Inferact's platform evolves.
SKILLS AND QUALIFICATIONS
Minimum qualifications:
- Bachelor's degree or equivalent experience in computer science, engineering, systems, machine learning, or similar.
- Strong software engineering ability in Python, Go, TypeScript, or similar, with experience building production-quality integrations, tooling, services, automation, or prototypes.
- Hands-on experience deploying or operating ML systems, model serving, AI infrastructure, cloud platforms, Kubernetes, or high-scale backend systems in production.
- Ability to work directly with sophisticated customer engineering teams, understand ambiguous technical environments, and personally drive implementations and debugging to resolution.
- Strong systems debugging skills across application, runtime, infrastructure, networking, identity, storage, observability, and distributed-system boundaries.
- Ability to reason about latency, throughput, batching, model/runtime compatibility, scaling, reliability, and cost tradeoffs in production inference environments.
- High ownership and strong technical communication, with the judgment to distinguish one-off customer work from problems that should become reusable product capabilities.
Preferred qualifications:
- Experience with vLLM, SGLang, TensorRT-LLM, TGI, Ray Serve, BentoML, or other LLM inference and model-serving systems.
- Experience with NVIDIA or AMD GPUs, CUDA / ROCm, GPU scheduling, multi-GPU serving, or accelerator-backed infrastructure.
- Experience deploying infrastructure software into enterprise, regulated, security-sensitive, or bring-your-own-cloud environments.
- Experience building APIs, SDKs, CLIs, developer tooling, deployment platforms, control planes, or infrastructure products used by technical teams.
- Experience profiling latency, throughput, concurrency, GPU utilization, bottlenecks, and performance regressions.
Bonus points if you have:
- Contributed to open-source ML systems, inference infrastructure, cloud infrastructure, Kubernetes, or developer tooling.
- Worked in a forward-deployed, customer engineering, field engineering, or highly technical solutions role where you personally wrote and shipped code.
- Built deployment playbooks, reference architectures, automation, or tooling that materially reduced customer time-to-production.
- Resolved severe customer-facing production issues that crossed multiple technical layers and required close partnership with core engineering.
- Turned repeated customer problems into reusable product features, abstractions, documentation, or platform improvements.
LOGISTICS
- Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.
- Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.
- Visa sponsorship: We sponsor visas on a case-by-case basis.
- Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.
Inferact, Inc. is an E-Verify company, and you may review the Notice of E-Verify Participation https://drive.google.com/file/d/1TWSDK2aZycxydMvPle230QSwuQtuNIyM/view?usp=sharing and the Right to Work posters in English and Spanish https://drive.google.com/file/d/1WxUM6hcXhb3CuJ_nWgnMmHF99XsuT9sI/view?usp=sharing.