Developer Relations Engineer

Superlinked; San Francisco (CA); On-site; USD 130,000 - 190,000; Full time

Job summary

Superlinked is seeking a hands-on DevRel Engineer to help ML engineers discover, try, and adopt the Superlinked Inference Engine (SIE). You will be close to the product and the community, building demos, talking to developers, shipping technical content, launching integrations, and turning feedback into better docs and product decisions.

This is a hands-on role focused on demos, tutorials, and community enablement, requiring clear communication of trade-offs and proactive developer engagement in

Qualifications

• Experience with ML infrastructure, LLM inference, or related developer tooling.
• Ability to read architecture, assess latency, cost, GPU utilization, and explain trade-offs clearly.
• Experience growing a developer product through open source, cloud, self-hosted, or hybrid models.

Responsibilities

• Make SIE easier to understand, try, and trust for ML engineers and platform teams.
• Build demos, examples, notebooks, quickstarts, and integration guides.
• Turn product updates and partner launches into useful technical content and co-marketing moments.
• Engage with users, answer technical questions, and relay feedback to engineering.
• Grow our OSS community via GitHub, workshops, hackathons, and talks.
• Build relationships with model, infrastructure, and ecosystem partners.
• Keep docs and onboarding up to date as SIE evolves.
• Collaborate with marketing on distribution, ensuring technical accuracy.

Skills

ML infra

LLM inference

Developer tools

Technical content

Open source

Community growth

Job description

About the role

We’re looking for a hands‑on DevRel Engineer to help more ML engineers discover, try, and adopt Superlinked Inference Engine (SIE).

You’ll be close to the product and the community: building demos, talking to developers, shipping technical content, launching integrations, and turning real feedback into better docs and product decisions.

This is a hands‑on role. You should be equally comfortable opening a PR, giving a talk, helping a developer debug their setup, and explaining a technical trade‑off clearly.

What you’ll do

• Make SIE easier to understand, try, and trust for ML engineers and platform teams.

• Build demos, examples, notebooks, quickstarts, and integration guides developers actually use.

• Turn new models, product updates, and partner launches into useful technical content and co‑marketing moments.

• Talk to users, answer technical questions, and bring recurring feedback back to engineering.

• Grow our OSS community through GitHub, workshops, hackathons, meetups, talks, and online communities.

• Build relationships with relevant model, infrastructure, and ecosystem partners.

• Keep our docs, examples, and developer onboarding up to date as SIE evolves.

• Work with marketing on distribution, while owning technical accuracy and developer relevance.

• Track what works: GitHub growth, installs, activation, developer feedback, event outcomes, and partner‑driven usage.

• Be active in the ML developer ecosystem, with a strong focus on San Francisco and the US, and occasional travel to major European events.

You’ll work closely with our founder in San Francisco and spend meaningful time in the local AI and ML community.

What we’re looking for

• You’ve worked with ML infrastructure, LLM inference, model fine‑tuning, or adjacent developer tools.

• You can read architecture, understand trade‑offs around latency, cost, GPU use, and reliability, and explain them without hand‑wav­ing.

• You’ve helped a developer product grow through real adoption, whether open source, cloud, self‑hosted, or a combination of these.

• You’re comfortable writing and modifying code.

• You’ve created technical content, demos, talks, workshops, or integrations that developers found genuinely useful.

• You’re proactive, quick to act, and good at spotting relevant community or partner opportunities.

• An existing AI/ML developer network is a plus.

What success looks like

You’ll help us build a stronger loop between product and developers: better examples, better feedback, more credible technical proof, and more developers successfully using SIE in real projects.