Research Engineer

About us We're reverse-engineering the origin of life — one of the great unsolved problems in science, and one we think AI finally makes tractable. We believe that understanding this transition, from geochemistry to biochemistry, will let us orchestrate molecular networks and build systems that are more capable, adaptive, efficient, and intelligent. If we succeed, the applications are vast: from catalysis and green synthesis to ab initio synthetic biology and programmable matter. Understanding and harnessing these processes could let ten billion of us thrive on this planet — and let us dream that diverse life keeps evolving and thriving beyond it. We're a small, diverse team of AI engineers, computational scientists, and bench scientists. We hold ourselves to the rigor of a research institute, but we ship like an engineering firm. Global team, HQs in Cambridge, MA and London, UK. The role You'll be a generalist research engineer, moving fluidly across our maintenance and research projects wherever leverage is highest. The through-line is using LLMs and agents to build software and complex systems — including for open-ended scientific questions, not just engineering ones. You'll have real latitude to decide what to build and how, and your work will land directly on how fast our researchers move and what our science can do. What you'll do Use LLMs and coding agents to build software and complex systems, and keep advancing the internal agentic systems we use to write our code and maintain our infrastructure Self-host and evaluate open-source models, and write the harnesses, tooling, and scaffolding that make agents reliable for our workflows Apply agents to scientific questions — an open-ended remit spanning genuine research, experimentation, and analysis, not only software development Contribute across a variety of maintenance and research projects as priorities shift, from internal tooling to data and model work Keep our cloud infrastructure and development environments healthy Essential experience Demonstrated ability to use LLMs to write software and build complex systems Hands-on experience with open-source models: self-hosting, evaluation, and writing harnesses or scaffolding around them Strong Python and the ability to own complex technical systems end to end Comfort working across an unfamiliar codebase and shipping in areas outside your prior expertise Sound engineering fundamentals: version control workflows, testing, and reproducible environments Highly preferred Background in biology, chemistry, or a related scientific domain Scientific computing or ML/research-tooling experience Substantial professional software engineering experience Experience building or operating agentic systems (multi-step tool use, orchestration, evaluation harnesses) Familiarity with cloud infrastructure (AWS or GCP), containerization, and infrastructure-as-code Logistics Compensation is highly competitive. We're also able to sponsor visas for the right candidate.