Staff Research Engineer

GitHub, Inc.•UNAVAILABLE, UNAVAILABLE

1d•Remote

About The Position

GitHub has changed the way software is built, and we have a unique opportunity to look further ahead to identify how software development can be faster, safer, easier, and more accessible. We’re looking for talented, experienced polymaths to join us in this mission! This is the rare role that affords both startup-level agency and a larger company’s resources. GitHub Next has incubated genre-defining products like Copilot, Copilot Workspace, Spark, Agentic Workflows, and more. You’ll work closely with a small group of experienced and talented researchers to explore the future of software development. Each exploration represents a risky bet that GitHub might want to make, and we have to support those bets with working prototypes. We then need to take those prototypes to market ourselves, and find evidence of product-market fit. Our prototypes (and the evidence we gather from the marketplace) inform GitHub’s leadership and roadmap. Please note that this is not an academic research role. Our job is to dream big about the future of software development and then build it. Our team feels like a permanent startup: every time we succeed, return to the drawing board to do it all over again. You can see many of our projects at githubnext.com.

Requirements

8+ years experience in software development, applied science, machine learning, or related field OR Bachelor's Degree in Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field AND 6+ years experience in software development, applied science, machine learning, or related field o OR Master's Degree in Machine Learning, Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field AND 4+ years experience in software development, applied science, machine learning, or related field o OR Doctorate in Machine Learning, Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field AND 2+ years experience in software development, applied science, machine learning, or related field OR equivalent experience.
Experience creating rapid prototypes that demonstrate a concept to stakeholders and enable decision making.
Experience identifying and justifying research goals in situations of ambiguity and executing towards those goals without explicit direction.

Nice To Haves

A deep understanding of GitHub’s industry and business, especially as it is affected by AI. Has experience communicating about these topics in a way that creates clarity and supplies nuance in a noisy marketplace.
Has held roles that deal with topics at the boundary of human knowledge regarding software development and developers.
Have significant experience with one of the many technology topics that are relevant to an interdisciplinary innovation group: frontend technologies (react/typescript/etc), backend technologies (infra/datastores/devops/security), ML & AI (prompts/retrieval/agentic systems/etc), programming languages, human-computer interaction, distributed systems.
Have significant experience with open-source software, communities, and the systems these communities use to self-organize and ship software for others.

Responsibilities

Research Engineers are makers who turn ambitious ideas into reliable prototypes. You will take loosely defined concepts and figure out how to make them real, scoping bets wisely and delivering value quickly. You will push AI capability limits, exploring what’s almost possible today and anticipating what will be common soon.
Exploration spans many technologies, requiring comfort reading source code, picking up new stacks, and identifying the technical pieces needed to build prototypes. You will operate as a generalist with deeper knowledge in some areas; hybrids thrive here, though specialists are also considered. You will help shape the data, signals, and features needed to support evolving prototypes.
GitHub Next runs on ideas, and strong communication drives team health and execution. You will collaborate to determine what work needs doing, split responsibilities, and move projects forward. Applies deep understanding of research approaches used across the team, organization, and industry to leverage (and not reinvent) solutions. Brings new technology and approaches into production by applying long-term research efforts to solve immediate product needs.
Builds and develops collaborative relationships within and outside the organization to share expertise and create business impact. Acts as a subject matter expert and provides consultative expertise to individuals across the organization in ascertaining technical feasibility of AI ideas/opportunities.
Assesses feasibility, builds small prototypes to prove viability, and engages in end-to-end AI development lifecycle (e.g., researching, prototyping, minimum viable product, product, improvement iterations, and maintenance). Provides guidance to less experienced team members conducting open-ended exploration without clear specs or pre-determined scope to inform feasibility considerationsAs agents take over more code generation, your value comes from judgment, creativity, and shaping high‑impact ideas.