Six Figure Work

Member of Technical Staff, Forward Deployed Engineer

Inferact

Company websiteinferact.ai (Inferact, opens in new tab)

Base salary $200K  to $400K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceOn-site
  • Status at last checkSource accepting applications when checked
  • Last checked (1 h ago) · observed since

About this 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 and the Right to Work posters in English and Spanish.

Source: Inferact on Ashby · View original posting (opens in new tab)

Pay in context

This role's base floor ($200,000) is above 58% of the 1,513 Data & ML roles in California listed on this site; 72 others list the same floor. Their median floor is $188,000; the middle half runs from $159,200 to $229,500.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.

This range next to 6 other live Inferact roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Inferact roles with the nearest advertised base floor
RolePublished base
Member of Technical Staff, Forward Deployed Engineer (this listing)$200K - $400K
Member of Technical Staff, Performance and Scale$200K - $400K
Engineering Manager$200K - $400K
Member of Technical Staff, Cloud Orchestration$200K - $400K
Member of Technical Staff, AMD GPU Kernel Engineering$200K - $400K
Member of Technical Staff, Developer Relations$200K - $400K
Member of Technical Staff, TPU Kernel Engineering$200K - $400K

Same $100K to $400K scale as every card. All Inferact roles · How to read the bar

Observed changes

  1. Began meeting the published-salary criteria
  2. First observed on the employer's board
Observed since
Employer-stated posting date
2026-10-02
Where this pay comes from

Location as the employer wrote it: San Francisco

USD 200,000 – 400,000 · 1 YEAR · Salary

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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