{"schemaVersion":"jobsearcher.job.v1","id":"ea8fc3b77be378b62e21be47","url":"https://jobsearcher.com/jobs/ea8fc3b77be378b62e21be47","canonicalUrl":"https://jobsearcher.com/jobs/ea8fc3b77be378b62e21be47","title":"RESEARCH ENGINEER (GENERAL)","description":"ABOUT THE COMPANY\nWe're building autonomous research agents for recursive self-improvement (multi-agent systems that propose, run, and analyze machine learning experiments). We're a small team based in San Francisco, on-site\nABOUT THE ROLE\nYou'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.\"\nYou'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.\nWHAT YOU'LL DO\nBuild and maintain the training, evaluation, and deployment pipelines that our research runs on\nTake research code from prototype to production: refactor, harden, instrument, test\nDesign observability into our research systems (metrics, logs, traces, eval dashboards) so failures surface fast\nOwn data pipelines for training and evaluation: ingest, dedup, version, validate\nWork closely with researchers to understand what they need, what's slow, and what's brittle\nSet engineering standards across our research stack (testing, reviews, runbooks) so the team scales\nContribute to architectural decisions that shape how research and production interact\nWHAT WE'RE LOOKING FOR\nSenior research engineer with 6+ years building production-grade research systems\nTrack record across the full lifecycle: data, training, evaluation, deployment, monitoring\nStrong distributed systems experience; you've shipped systems that have to be on\nFluent Python, fluent with at least one of (PyTorch, JAX); comfortable at the systems-level when needed\nComfortable with experimentation infrastructure (Ray, Slurm, Kubernetes, or similar)\nBias toward shipping; you prefer working code over working diagrams\nStrong written communication\nNICE TO HAVE\nExperience building experimentation platforms or research infrastructure at a frontier research lab\nBackground in distributed training systems\nOpen-source contributions to research infrastructure\nHistory of working effectively with small senior teams\nTHIS ROLE IS PROBABLY NOT FOR YOU IF\nYou want to do research with engineering as a side activity: this is engineering as the main thing\nCross-functional work with researchers (translation, scoping, education) doesn't appeal\nLong-running ownership of running systems isn't appealing: this role has it","company":"Makermaker","rawCompany":"makermaker","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-04T17:04:04.202Z","occupations":[{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"RESEARCH ENGINEER (GENERAL)","description":"ABOUT THE COMPANY\nWe're building autonomous research agents for recursive self-improvement (multi-agent systems that propose, run, and analyze machine learning experiments). We're a small team based in San Francisco, on-site\nABOUT THE ROLE\nYou'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.\"\nYou'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.\nWHAT YOU'LL DO\nBuild and maintain the training, evaluation, and deployment pipelines that our research runs on\nTake research code from prototype to production: refactor, harden, instrument, test\nDesign observability into our research systems (metrics, logs, traces, eval dashboards) so failures surface fast\nOwn data pipelines for training and evaluation: ingest, dedup, version, validate\nWork closely with researchers to understand what they need, what's slow, and what's brittle\nSet engineering standards across our research stack (testing, reviews, runbooks) so the team scales\nContribute to architectural decisions that shape how research and production interact\nWHAT WE'RE LOOKING FOR\nSenior research engineer with 6+ years building production-grade research systems\nTrack record across the full lifecycle: data, training, evaluation, deployment, monitoring\nStrong distributed systems experience; you've shipped systems that have to be on\nFluent Python, fluent with at least one of (PyTorch, JAX); comfortable at the systems-level when needed\nComfortable with experimentation infrastructure (Ray, Slurm, Kubernetes, or similar)\nBias toward shipping; you prefer working code over working diagrams\nStrong written communication\nNICE TO HAVE\nExperience building experimentation platforms or research infrastructure at a frontier research lab\nBackground in distributed training systems\nOpen-source contributions to research infrastructure\nHistory of working effectively with small senior teams\nTHIS ROLE IS PROBABLY NOT FOR YOU IF\nYou want to do research with engineering as a side activity: this is engineering as the main thing\nCross-functional work with researchers (translation, scoping, education) doesn't appeal\nLong-running ownership of running systems isn't appealing: this role has it","datePosted":"2026-08-04T17:04:04.202Z","dateModified":"2026-08-04T17:04:04.202Z","hiringOrganization":{"@type":"Organization","name":"Makermaker","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ea8fc3b77be378b62e21be47"},"url":"https://jobsearcher.com/jobs/ea8fc3b77be378b62e21be47"}}