AI Engineer | Dayhoff Labs

Dayhoff Labs

AI Engineer

Location: Cambridge, MA or London, UK
Start Date: Immediate
Position Type: Full-time

About the Role

At Dayhoff we're reverse engineering the chemistry of life from its origins. We're seeking an AI engineer to help design and train frontier models in biology and chemistry — spanning molecular structure and dynamics, reactions, and reaction networks. You'll work at the intersection of machine learning and biochemistry in a highly collaborative environment, where model development directly informs and is informed by experimental work in our wet labs.

What You'll Do

Design and train large-scale AI models across three core research threads: enzyme–substrate prediction, neural network potentials, and inverse design of chemical and biochemical reaction networks
Own model development end-to-end, from architecture and data pipeline decisions through training, debugging, and evaluation
Work hand-in-hand with chemists and biochemists, translating between AI and chemistry in both directions
Collaborate with leading international labs and integrate experimental feedback into model iteration
Take ownership of challenging problems with incomplete information and deliver results under tight timelines

What We're Looking For

Essential Experience:

Demonstrated experience training large models end-to-end, with the depth to discuss in detail what broke and how you fixed it
Strong ML engineering fundamentals: architectures, training dynamics, data pipelines, and evaluation
Ability to communicate complex technical concepts clearly to colleagues whose first language is chemistry rather than AI

Highly Preferred:

PhD in a quantitative field (common on our team, but depth matters more than credentials)
Experience in ML-for-chemistry or ML-for-biology (e.g., neural network potentials, graph neural networks, protein or reaction models)
Familiarity with computational chemistry or biochemistry concepts and workflows

Essential Qualities:

High Agency: You see problems and solve them without waiting for detailed instructions. You own outcomes.
Engineering Mindset: You build robust, reproducible training pipelines and think systematically about scalability.
Scrappy: You're resourceful, adaptable, and comfortable working with imperfect data or incomplete theoretical frameworks.
Risk-Taking: You're willing to pursue unconventional approaches and aren't paralyzed by the possibility of failure.
Collaborative: You thrive in tight feedback loops and actively seek input from diverse expertise across AI, chemistry, and biology.

Why This Role is Different

The bet we're making is that the origin of life isn't a curiosity question; it's the missing chapter of biochemistry, and writing it gives us models the rest of the field can't build. You'll work across wet and dry labs in Boston and London, alongside AI researchers, engineers, chemists, and biochemists, with the freedom to pursue high-risk, high-reward approaches. Compensation and equity are competitive for our home markets, and we can discuss relocation and visa sponsorship for the right candidates.

Apply

Send your resume or CV to careers@dayhofflabs.com along with:

One paper from the last 18 months in ML-for-chemistry or ML-for-biology that you think matters, and one you think is overrated — a paragraph on each.
Something you've built that you're proud of: link, repo, or short description.