---
title: 'Member of Technical Staff, Forward Deployed Engineer at Inferact'
canonical: 'https://feeny.ai/job/member-of-technical-staff-forward-deployed-engineer-inferact-san-francisco-a1wq0bc1fbfk'
type: 'job'
last_seen: '2026-10-13'
---

# Member of Technical Staff, Forward Deployed Engineer at Inferact

- **Company:** Inferact
- **Location:** San Francisco, CA
- **Compensation:** $200k–$400k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-02
- **Last confirmed live:** 2026-10-13
- **Apply:** https://jobs.ashbyhq.com/inferact/b127864f-5c71-4c96-90ce-cb20c57391a9

## Job description

## 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.

## About Inferact

## Company Overview
- **One-liner**: Inferact is a startup founded by the creators of vLLM, the leading open-source LLM inference engine, dedicated to making AI inference cheaper and faster at global scale.
- **Entity Type**: Private (Seed stage; raised $150M in seed funding)
- **Headquarters**: San Francisco, California, United States (with a second office in Singapore)
- **Founded**: 2025
- **Founders**: Simon Mo (CEO), Woosuk Kwon, Kaichao You (Chief Scientist), Roger Wang, Joseph Gonzalez, Ion Stoica

## Core Business
- **Primary industry**: AI infrastructure / open-source inference engine for large language models
- **Target customers**: AI labs, hyperscalers, startups, and enterprises deploying large-scale AI models (B2B, primarily technical teams)
- **Mission**: Grow vLLM as the world’s AI inference engine and accelerate AI progress by making inference cheaper and faster.

## Products & Services
- **vLLM (Open-Source Inference Engine)**: The core product – an open-source LLM inference engine that supports 500+ model architectures and runs on 200+ accelerator types. Inferact stewards and supercharges vLLM, with all optimizations flowing back to the community.
- **Managed Inference Infrastructure (in development)**: Inferact is building infrastructure to absorb the complexity of deploying frontier models at scale, aiming to make it as simple as spinning up a serverless database.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Total funding of $150M (seed round, announced 2026)
- **Notable Investors/Partners**: Lightspeed Venture Partners (lead), Redpoint Ventures, Andreessen Horowitz, Altimeter Capital, Sequoia Capital, The House Fund, GC&H Investments, and others. Partnerships include NVIDIA, Red Hat, DigitalOcean, and Cohere.
- **Growth Signals**: 
  - $150M seed round – one of the largest seed rounds in AI infrastructure.
  - 22 employees with +27.3% monthly headcount growth.
  - vLLM ecosystem: 2,000+ contributors, 500+ model architectures, 200+ accelerator types.
  - Day-zero support for new model architectures (e.g., Cohere’s Command A+) and hardware integrations.
  - Active hiring with 5 open positions across inference, performance, kernel engineering, and cloud orchestration.

## Competitive Advantages
- **Deep ecosystem moat**: vLLM is the de facto standard open-source inference engine, with a massive community and integrations across models and hardware that took years to build.
- **Founding team credibility**: Creators and core maintainers of vLLM, with experience deploying at frontier scale (research and production).
- **Hardware-software co-optimization**: Positioned at the intersection of model innovation and hardware diversity, enabling day-zero compatibility and performance optimizations.
- **Open-source commitment**: All improvements flow back to vLLM, ensuring community trust and rapid adoption.

## Strategic Focus
- **Current priorities**: Push vLLM performance further, deepen support for emerging model architectures (MoE, multimodal, agentic), expand hardware coverage (200+ accelerators), and build managed infrastructure to simplify deployment.
- **Growth direction**: Close the capability gap between models and serving systems; absorb complexity so teams can focus on innovation rather than infrastructure.

## Why Work Here
- **Culture**: High-caliber engineering team with roots in vLLM, PyTorch, and top AI labs. Emphasis on open-source contribution and cutting-edge inference research.
- **Work policy**: Hybrid with a San Francisco HQ; at least one open role (Member of Technical Staff, Exceptional Generalist) is listed as Remote.
- **Notable perks**: Opportunity to work at the frontier of AI inference, directly impact the open-source ecosystem, and collaborate with partners like NVIDIA, Red Hat, and major AI labs.
- **Engineering culture**: Strong focus on systems engineering, kernel optimization, and cloud orchestration – ideal for engineers passionate about performance and infrastructure.

## Sources
1. [inferact.ai](https://inferact.ai/)
2. [LinkedIn](https://www.linkedin.com/company/inferact)
3. [CB Insights](https://www.cbinsights.com/company/inferact)
4. [Sequoia Capital](https://sequoiacap.com/companies/inferact/)
5. [Ashby Jobs](https://jobs.ashbyhq.com/inferact)

## Other roles at Inferact

- [Strategic Finance Lead](https://feeny.ai/job/strategic-finance-lead-inferact-san-francisco-8w870avftckq) — San Francisco, CA
- [Controller](https://feeny.ai/job/controller-inferact-san-francisco-8ccr4mehhhdv) — San Francisco, CA
- [Member of Technical Staff, Vulnerability Management](https://feeny.ai/job/member-of-technical-staff-vulnerability-management-inferact-san-francisco-28n91fzms5pv) — San Francisco, CA
- [Enterprise Partnerships Manager](https://feeny.ai/job/enterprise-partnerships-manager-inferact-san-francisco-56fh7h15hft3) — San Francisco, CA
- [GTM Engineer](https://feeny.ai/job/gtm-engineer-inferact-san-francisco-4kw95nqkxq2p) — San Francisco, CA
- [Graphic Designer](https://feeny.ai/job/graphic-designer-inferact-san-francisco-vrkzf7acr3fg) — San Francisco, CA
- [Social Media Manager](https://feeny.ai/job/social-media-manager-inferact-san-francisco-8265d2aybdpm) — San Francisco, CA
- [Technical Product Marketing Manager](https://feeny.ai/job/technical-product-marketing-manager-inferact-san-francisco-ts8bahbsbvv7) — San Francisco, CA
- [Field Marketing Manager](https://feeny.ai/job/field-marketing-manager-inferact-san-francisco-ve91k1kbsy1y) — San Francisco, CA
- [Member of Technical Staff, Cluster Administration](https://feeny.ai/job/member-of-technical-staff-cluster-administration-inferact-singapore-98dzry95tnmf) — Singapore