Senior Machine Learning Engineer, Small Molecules

About Boltz

Boltz is a public benefit company building the next generation of AI-powered molecular modeling tools to make biology programmable and accelerate drug discovery, while keeping frontier capabilities broadly accessible.

Boltz began as an MIT spin-out. Our founders built Boltz-1 at MIT, and it became the first fully open-source model to match AlphaFold 3's accuracy in predicting the 3D structure of biomolecular complexes.

We focus on two things

• Open foundation models. Boltz-1, Boltz-2, and BoltzGen are open models trusted by 100,000+ scientists across biotech and academia, and used in programs at every Top 20 pharma as well as leading agrichemical and industrial research organizations.
• Boltz Lab. Our commercial platform runs our latest models and design agents as reliable, production-grade tools built around real chemistry and biology workflows. Teams start from a target and a hypothesis, then generate, evaluate, and rank candidate molecules, while we provide the compute, infrastructure, and collaboration layer so their scientists can move faster.

The two feed each other: open-source adoption earns scientific credibility and community insight, and Boltz Lab turns that into real impact on our partners' discovery programs.

You can read more about our mission, research and product vision in our manifesto.

About the role

As a Machine Learning Engineer on Small Molecules, you will own the engineering that turns our small-molecule models into fast, reliable pipelines, from training and evaluation to the design workflows partners run in Boltz Lab. Our next model, BoltzMol-2, has to work at scale on real hit-finding and hit-optimization programs, and that depends on the pipelines around it as much as the model itself.

You will work closely with the Small Molecules team's research and cheminformatics scientists, Research Engineering, our Product and Platform engineers, and our pharma and biotech partners.

This role is ideal for an engineer who likes owning ML systems end to end and wants to see them used on real discovery programs.

What you'll do

• Build and maintain training, fine-tuning and evaluation pipelines for our small-molecule models.
• Build scalable design pipelines: generate, score, filter and rank millions of molecules with consistent, reproducible outputs.
• Take small-molecule models and workflows from research into Boltz Lab, with Product and Platform engineers.
• Run and adapt pipelines on partner data for pilots and customer projects, and deliver results on time.
• Feed what you learn about performance, failure modes and usability back to research scientists and the product team.

About you

Minimum Requirements

• Senior or Staff-level experience building and shipping machine learning systems in production.
• Strong Python and PyTorch, and experience with distributed or high-throughput ML workloads on GPUs.
• Solid software engineering fundamentals: clean, tested, maintainable code and reproducible pipelines.
• A track record of taking models from research to production or to real users.
• Working knowledge of molecular ML or cheminformatics (e.g. RDKit, molecular representations), and comfort working with chemists and researchers.

Preferred Requirements

• Experience on drug discovery programs, or with binding, screening or protein–ligand structural data.
• Experience with workflow orchestration, Kubernetes or cloud GPU infrastructure; early-stage startup experience.
• Experience using Boltz models, or open-source contributions.

We know great people don't always tick every box. If this role excites you and you meet most of the minimum requirements, we'd like to hear from you.

What we offer

• Build the pipelines that put our small-molecule models in front of leading discovery teams.
• Work alongside one of the most talent-dense teams in the field.
• Significant ownership and independence, with responsibility for driving projects from concept to deployment.
• Highly competitive salary with meaningful equity in a public benefit company.
• Benefits:
• 25 days plus bank holidays a year
• Annual team offsite trip
• Private healthcare (BUPA), covering pre-existing conditions
• Pension program
• Paid parental leave
• Wellhub gym membership
• Free lunch every day
• Travel expenses

How we hire

1. Initial screen with a member of the Talent team
2. Technical interview
3. Onsite in London or virtual onsite with the team
4. Offer + Onboarding

Our commitment

Boltz is committed to building a diverse team and an inclusive workplace. We welcome applicants of all backgrounds. If you need any adjustments during the hiring process, tell us at [email] and we'll make it work.