Member of Technical Staff, Developer Relations
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
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (21 min 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 Developer Relations Engineer to help make vLLM the default way developers understand, build, and scale AI inference. This is not a generic DevRel role. We're looking for a inference systems educator-builder: someone who can understand vLLM as a deep LLM inference systems project, teach hard technical concepts clearly, and create public artifacts that help practitioners build better systems.
You'll write technical deep dives, build demos, create tutorials, contribute to docs and examples, host workshops, and help developers understand topics like KV cache, continuous batching, prefix caching, prefill and decode, quantization, GPU serving, latency versus throughput, and model-server tradeoffs across vLLM and adjacent systems. Your work will shape how the broader AI infrastructure community learns, adopts, and builds with vLLM.
Skills and Qualifications
Minimum qualifications:
Bachelor's degree or equivalent experience in computer science, engineering, machine learning, systems, or similar.
Strong technical understanding of LLM inference systems, model serving, GPU inference, distributed runtimes, scheduling, batching, quantization, or related infrastructure.
Ability to credibly explain systems concepts such as KV cache, PagedAttention, continuous batching, prefill / decode scheduling, prefix caching, speculative decoding, tensor parallelism, data parallelism, or latency versus throughput tradeoffs.
Experience with vLLM or adjacent inference technologies such as SGLang, TensorRT-LLM, TGI, LoRAX, Ray Serve, FlashInfer, BentoML, Baseten-style serving platforms, or similar systems.
A strong public portfolio of technical artifacts, such as blogs, tutorials, workshops, courses, OSS docs, benchmark posts, architecture explainers, conference talks, demos, or runnable repositories.
Ability to write and teach for practitioners without sounding like a content marketer.
Strong engineering judgment, product taste, and ability to turn raw technical material into useful developer education.
Preferred qualifications:
Prior work in ML systems, distributed systems, HPC, compilers, GPU kernels, serving infrastructure, MLOps, developer tooling, or open-source infrastructure.
Experience creating technical content that teaches reusable mental models, not just product features.
Experience contributing to developer-facing open source through docs, tutorials, examples, cookbooks, demos, or community support.
Existing credibility or community presence in AI infrastructure, OSS, CUDA / GPU, Ray, vLLM, PyTorch, Modal, BentoML, Baseten, Predibase, Together AI, Anyscale, LMSYS, or similar ecosystems.
Ability to host workshops, create hands-on labs, present technical talks, and help developers move from concept to working code.
Bonus points if you have:
Written widely-shared technical blogs, courses, or architecture deep dives on LLM inference, model serving, GPU serving, or ML systems.
Built demos, benchmarks, tutorials, or repositories around vLLM, SGLang, TensorRT-LLM, TGI, Ray Serve, FlashInfer, or related systems.
Contributed to open-source ML infrastructure, inference systems, developer tooling, or technical education projects.
Created practitioner-facing content with code, diagrams, benchmarks, demos, or end-to-end labs.
Built a durable personal portfolio that demonstrates technical depth, taste, and a strong point of view.
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 71% of the 4,309 Software Engineering roles in California listed on this site; 146 others list the same floor. Their median floor is $176,000; the middle half runs from $149,100 to $202,000.
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 listingMember of Technical Staff, Developer Relations$200K to $400K
Member of Technical Staff, Performance and Scale$200K to $400K
Engineering Manager$200K to $400K
Member of Technical Staff, Cloud Orchestration$200K to $400K
Member of Technical Staff, AMD GPU Kernel Engineering$200K to $400K
Member of Technical Staff, Forward Deployed Engineer$200K to $400K
Member of Technical Staff, TPU Kernel Engineering$200K to $400K
Chart as a table
| Role | Published base |
|---|---|
| Member of Technical Staff, Developer Relations (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, Forward Deployed Engineer | $200K - $400K |
| Member of Technical Staff, TPU Kernel Engineering | $200K - $400K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-06-17
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.
