Job Opportunities API

The Public Ledger of Openings

← Back to the ledger

Research Engineer, Operations

Basis Research
CompanyBasis Research
CategoryEngineering
LocationNew York
RemoteOn-site
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted23 Nov 2025
Last verified30 Jul 2026
SourceEmployer career page (ashby)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
ABOUT BASIS Basis https://www.basis.ai is a nonprofit applied AI research organization with two mutually reinforcing goals. The first is to understand and build intelligence. This means to establish the mathematical principles of what it means to reason, to learn, to make decisions, to understand, and to explain; and to construct software that implements these principles. The second is to advance society’s ability to solve intractable problems. This means expanding the scale, complexity, and breadth of problems that we can solve today, and even more importantly, accelerating our ability to solve problems in the future. To achieve these goals, we’re building both a new technological foundation that draws inspiration from how humans reason, and a new kind of collaborative organization that puts human values first. ABOUT THE ROLE Research Engineers in Operations at Basis build the internal tooling, automation, and measurement systems that multiply researcher productivity and operational efficiency. You will create tools that save hours of manual work, automate proposal and CRM workflows, and provide analytics that inform strategic decisions as Basis scales. We are looking for people who excel technically and understand research workflows deeply enough to identify high-leverage automation opportunities. The ideal Research Engineer has experience translating research ideas into robust code, building LLM-powered automation systems, and creating tools that researchers actually want to use. You will build everything from researcher productivity tools to GTM automation to analytics infrastructure. This role is critical to Basis’s scaling strategy. You will be among the first to transform Basis operations from manual processes to automated systems that enable growth without diminishing returns. We seek individuals who excel technically and value probing concepts at their foundations. Our research engineers aspire to build rigorous, high-quality, robust tools, unafraid to tinker, make mistakes, and explore radically different ideas to achieve this. Basis is a collaborative effort, both internally and with our external partners; we are looking for people who enjoy enabling others to accomplish work at scales they couldn’t reach alone. WE EXPECT YOU TO: - Possess excellent programming and software engineering skills, especially in Julia, Python, C++, ML-family languages. Have demonstrated the ability to drive software projects from start to finish. - Be comfortable digesting research from PL and/or ML venues, such as PLDI, POPL, NeurIPS, or ICML. Progress with a high degree of autonomy and under uncertainty. - Have experience with LLM-powered automation, including using language models (OpenAI API, Anthropic Claude, LangChain) for intelligent automation, workflow orchestration, and agent-based systems. - Have demonstrated significant technical achievements within ML engineering. Examples include: - You’ve implemented variants of newly published techniques from scratch - You build systems and workflows for training large models distributed across many machines - You’ve built systems that span all levels of the programming stack from high-level API infrastructure to close-to-the-metal code - Understand research and operational workflows well enough to identify high-impact automation opportunities. You might have worked in research environments, built productivity tools, or supported technical teams through infrastructure. - Be skilled at user-centric design for internal tools. You naturally seek user feedback, iterate based on real usage, and measure success by adoption and time saved rather than technical sophistication. - Be excited about force-multiplying impact. The tools you build might not be externally visible, but they enable Basis to solve intractable problems at scales we couldn’t otherwise reach. RESPONSIBILITIES: - Build researcher productivity tools includ
HOUSE ADYou found the opening. Now track it.Tracker, radar and AI drafts in one place.erioun.com →