# Platform Engineer at Goodfire > United States · Unspecified · Backend · open. Source: https://alderhq.app/jobs/greenhouse%3Agoodfire%3A5253335008 (read 2026-11-06). ## Facts (observed) - Company: [Goodfire](https://alderhq.app/companies/goodfire) - Location text: San Francisco, CA; San Francisco - Where it can be done from (inferred): United States (evidence: "Location: San Francisco, CA; San Francisco") - Posted: 2026-06-10 (150 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://job-boards.greenhouse.io/goodfire/jobs/5253335008 - Skills listed (inferred): Distributed systems ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (SF Bay Area, n 117): p25 $187k, median $217k, p75 $265k ## Description (the employer's text) ### About Goodfire Goodfire is an AI interpretability research lab. We build interpretability agents and infrastructure to understand, monitor, and align AI models. We believe that AI is the most consequential technology of our time. Yet AI models are trained by trial and error today, with limited understanding of what drives their behavior. Our goal is to advance the research and technology needed to fully understand and align AI so humanity can trust superintelligence. Goodfire is a public benefit corporation founded by researchers who helped pioneer the field of interpretability at OpenAI and Google DeepMind. We are headquartered in San Francisco and have raised over $200M from leading investors including Lightspeed, Menlo, and B Capital. ### About the role We’re looking for Platform Engineers to build the infrastructure and services behind Goodfire’s interpretability platform. You’ll help researchers and engineers run experiments, work with model data, and bring new capabilities into production. You’ll build shared systems for model analysis, training, inference, and monitoring, making them reliable, reproducible, and straightforward to use. Working closely with researchers, ML engineers, and product engineers, you’ll turn evolving research workflows into platform capabilities that support both internal research and customer products. ### What you’ll do - Build shared services and APIs: create the foundations that research tools and customer products use to launch work, access data, and retrieve results. - Support compute-intensive workflows: build systems for scheduling, tracking, and recovering long-running experiments and model workloads. - Make data and artifacts usable: develop pipelines and storage interfaces for datasets, model activations, checkpoints, and evaluation results, with clear provenance and reproducibility. - Own production reliability: improve deployment, observability, performance, and failure recovery across platform services. - Improve developer experience: make it easier for researchers and engineers to develop, test, and ship new capabilities without rebuilding infrastructure for each project. We’ll work with you to determine the initial area of ownership that best matches your experience and strengths. ### What you’ll bring ### Required experience - 2+ years of experience building and operating production software. - Strong backend or systems engineering fundamentals, with depth in areas such as distributed systems, data infrastructure, cloud infrastructure, or developer tooling. - Experience owning a service or infrastructure component through development, deployment, and ongoing operation. - Ability to debug failures and reason about performance, reliability, and maintainability across system boundaries. - Comfort translating evolving research and engineering needs into practical technical solutions. - Interest in understanding how AI models work and building the systems that make that understanding useful. ### Preferred qualifications - Experience supporting ML training, inference, evaluation, or research workflows. - Experience with job orchestration, GPU workloads, or large-scale data processing and storage. - Experience building shared infrastructure or developer tools used by other engineering teams. - Startup or frontier lab experience in fast-moving teams. ### Our values Goodfire is looking for individuals who embody our values and share our deep commitment to making interpretability accessible. We are building a team first and foremost. ### Put mission and team first All we do is in service of our mission. We trust each other, deeply care about the success of the organization, and choose to put our team above ourselves. ### Improve constantly We are constantly looking to improve every piece of the business. We proactively critique ourselves and others in a kind and thoughtful way that translates to practical improvements in the organization. We are pragmatic and consistently implement the obvious fixes that work. ### Take ownership and initiative There are no bystanders here. We proactively identify problems and take full responsibility over getting a strong result. We are self-driven, own our mistakes, and feel deep responsibility over what we’re building. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Agoodfire%3A5253335008 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.