Research Engineer
Dayhoff Labs
Research Engineer
Dayhoff Labs
AI-driven molecular design and simulation
We're reverse-engineering the origin of life — one of the great unsolved problems in science, and one we think AI finally makes tractable. Understanding this transition, from geochemistry to biochemistry, is what will let us orchestrate molecular networks and build systems that are more capable, adaptive, and efficient.
If we succeed, the applications are vast: catalysis, green synthesis, ab initio synthetic biology, programmable matter. Understanding and harnessing these processes could let ten billion of us thrive on this planet — and let life keep evolving beyond it.
We're a small, diverse team of AI engineers, computational scientists, and bench scientists. We ship fast and iterate quickly. Global team, HQs in Cambridge, MA and London, UK.
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.
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
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
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), containerisation, and infrastructure-as-code
We're able to sponsor visas for the right candidate.
AI-driven molecular design and simulation
Dayhoff Labs develops AI models and computational platforms to solve complex problems in chemistry, biochemistry, and synthetic biology. Its tools help researchers design, optimize, and simulate molecules such as enzymes and catalysts, enabling faster discovery and more sustainable chemical processes. By combining machine learning, computational chemistry, and laboratory work, it offers machine-assisted workflows that integrate experimental data and collaboration with researchers, with a strong emphasis on open science. The company aims to shorten discovery timelines, reduce costs and environmental impact, and broaden access to AI-powered molecular design for academia and industry.
Explore more opportunities at Dayhoff Labs