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Founding Developer Relations Engineer

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Goaly
Full Time position
Listed on 2026-10-13
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 200000 USD Yearly USD 120000.00 200000.00 YEAR
Job Description & How to Apply Below
ABOUT US

We're building toward a world where every company can become its own AI lab.

Goaly is a stealth AI startup founded by ex-Meta Superintelligence Labs engineers and researchers. Our mission is to dramatically lower the cost, time, and talent barriers to building proprietary AI — and make each generation of models faster and cheaper to build than the last.

Backed by leading AI investors and endorsed by frontier AI researchers and builders, we're looking for an engineer who can build in public, explain hard systems clearly, and already knows how to reach the people who train models.

ABOUT

THE ROLE

Goaly's users are the people who run post-training: the ML infra engineers and researchers who babysit SFT, RL, and fine-tuning jobs on GPU clusters. They don't read marketing. They read benchmarks, repos, docs, and the engineer who wrote them. You will be that engineer.

You will be our first Developer Relations hire and the technical voice of Goaly as we come out of stealth. Half of your week is building: running real post-training workloads on our stack, writing the benchmark harnesses, example integrations, and docs that get a stranger from zero to a first result in thirty minutes. The other half is making sure the right ten thousand people see it: engineering posts, talks, open-source releases, and the one-on-one conversations with practitioners that turn into design partners and hires.

This is not a marketing role with a technical veneer, and it is not an engineering role that occasionally posts. You need to be credible in a room full of people who train models, and you need an audience in that room — or a proven ability to build one.

This is a founding role. You will report to the founders and work daily with engineering and the go-to-market team. There is no playbook yet; you help write it.

WHAT YOU'LL DO
  • Build the signature technical artifacts. Own a public post-training efficiency benchmark, reproducible before/after case studies (doomed-run kills, silent throughput regressions, dollars per eval point), and the open-source tools we release around them.

  • Write the docs that convert. Quickstarts, reference docs, and example integrations for the stacks our users actually run (PyTorch distributed, Megatron, FSDP, Torch Titan, Ray, Slurm, Kubernetes on GPUs, W&B, MLflow) so an engineer can get a read-only Retroactive Kill Report on their own cluster without talking to us.

  • Create technical content practitioners share. Deep-dive engineering posts, benchmark write-ups, failure-mode teardowns ("seven ways an RL run dies silently"), short demo videos, and live walkthroughs.

  • Own distribution. Run Goaly's technical presence on X, Linked In, Git Hub, Hacker News, and the ML-infra Discord and Slack communities. Land talks at the venues our users attend (PyTorch Conference, MLSys, Ray Summit, GTC, NeurIPS and ICML workshops, Bay Area AI infra meetups). Build relationships with the people whose posts our audience already reads.

  • Be the feedback loop. Sit with design partners, reproduce their problems on our stack, and bring engineering precise, prioritized feedback. Turn repeated questions into docs, tools, or product changes.

  • Build community around the problem, not the product. Practitioner conversations, office hours, and a newsletter or series that becomes the place to learn about post-training efficiency.

  • Amplify the founders. Turn the founding team's Llama post-training infra experience into content and talks, and work with the GTM team to turn attention into design-partner pipeline and candidate pipeline.

  • Measure and cut. Track reach, repo adoption, docs funnel, inbound design-partner requests, and hires sourced. Double down on what works and kill what doesn't.

YOU MAY BE A GOOD FIT IF YOU HAVE
  • A real…

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