Posting record
Open 12+ days
- Makermaker.ai's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Makermaker.ai, so its true age is longer.
Last checked Nov 2, 2026.
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Upload your resumeWhat the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
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Skills mentioned
About the role
ABOUT THE COMPANY
We're building autonomous research agents for recursive self-improvement (multi-agent systems that propose, run, and analyze machine learning experiments). We're a small, well-funded team that works onsite in San Francisco.
ABOUT THE ROLE
You'll build and maintain the research systems and pipelines that our research runs on top of: data pipelines, training infrastructure, evaluation tooling, deployment, observability. The work bridges research and production, and you'll be the person who makes "we ran an experiment" actually mean "we ran it correctly, at scale, with results we trust."
You'll own systems end-to-end. You'll work with researchers daily and translate research code into infrastructure that the team can rely on. You'll move fast and you'll be measured on whether your systems make the team faster.
WHAT YOU'LL DO
- Build and maintain the training, evaluation, and deployment pipelines that our research runs on
- Take research code from prototype to production: refactor, harden, instrument, test
- Design observability into our research systems (metrics, logs, traces, eval dashboards) so failures surface fast
- Own data pipelines for training and evaluation: ingest, dedup, version, validate
- Work closely with researchers to understand what they need, what's slow, and what's brittle
- Set engineering standards across our research stack (testing, reviews, runbooks) so the team scales
- Contribute to architectural decisions that shape how research and production interact
WHAT WE'RE LOOKING FOR
- Senior research engineer with 6+ years building production-grade research systems
- Track record across the full lifecycle: data, training, evaluation, deployment, monitoring
- Strong distributed systems experience; you've shipped systems that have to be on
- Fluent Python, fluent with at least one of (PyTorch, JAX); comfortable at the systems-level when needed
- Comfortable with experimentation infrastructure (Ray, Slurm, Kubernetes, or similar)
- Bias toward shipping; you prefer working code over working diagrams
- Strong written communication
NICE TO HAVE
- Experience building experimentation platforms or research infrastructure at a frontier research lab
- Background in distributed training systems
- Open-source contributions to research infrastructure
- History of working effectively with small senior teams
THIS ROLE IS PROBABLY NOT FOR YOU IF
- You want to do research with engineering as a side activity: this is engineering as the main thing
- Cross-functional work with researchers (translation, scoping, education) doesn't appeal
- Long-running ownership of running systems isn't appealing: this role has it
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