---
title: 'Computational Biologist at Boltz'
canonical: 'https://feeny.ai/job/computational-biologist-boltz-london-ywq0h6gna1qr'
type: 'job'
last_seen: '2026-09-13'
---

# Computational Biologist at Boltz

- **Company:** Boltz
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-08-12
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.gem.com/boltz/am9icG9zdDruG7aY4CV29CQvK8pSEaCQ

## Job description

## About Boltz

Boltz is a public benefit company building the next generation of AI-powered molecular modelling tools to make biology programmable and accelerate drug discovery, while keeping frontier capabilities broadly accessible. Boltz-1, Boltz-2 and BoltzGen are open models trusted by scientists across biotech and academia, and used in programs at leading pharmaceutical, agricultural, and industrial research organisations. We believe that breakthroughs in biology will increasingly come from the combination of large-scale biological data, machine learning, and mechanistic understanding. Our mission is to build the tools that enable scientists to make those breakthroughs faster.

## About the Role

We are looking for a Computational Biologist to work at the intersection of protein design, computational biology, and machine learning, with a particular focus on antibodies, peptides, and other protein therapeutics.

You will support both Boltz's internal research and external drug discovery programs. You will work directly with our clients and scientific partners to understand their design problems, apply Boltz's models to their programs, analyse their computational and experimental data, and help them design and optimise antibodies, peptides, and other protein therapeutics. At the same time, you will work closely with our Research and ML teams to turn our foundation models into robust, end-to-end protein design and optimisation pipelines, combining models for generation, structure prediction, sequence design, scoring, developability, and candidate selection into workflows that can be applied reliably to real design problems.

A core part of the role is working with large-scale protein sequence and structural data. You will analyse natural, generated, and experimentally tested proteins using sequence and structural similarity, clustering, alignment, interface analysis, diversity selection, and other computational approaches. You will use these analyses to understand design space, select candidates for experimental testing, build rigorous evaluation datasets, and help both our internal teams and clients understand where our models succeed and fail.

You will also close the loop between computational design and experiment. As antibodies, peptides, and other designed proteins are experimentally tested, you will perform retrospective analyses of binding, affinity, expression, stability, developability, and other measurements, connecting experimental outcomes back to computational predictions and individual stages of the design pipeline. You will work with clients to interpret these results and determine how they should inform subsequent design rounds, while using the same insights internally to improve our models, ranking methods, and design pipelines.

This is a highly hands-on computational role. You will be expected to write strong scientific software, run and understand modern protein design and optimisation methods, build reproducible pipelines around them, and develop the analyses needed to interrogate their outputs. The ideal candidate combines strong programming ability with a deep understanding of protein sequence and structure, and is comfortable moving between internal research and client-facing scientific work, exploratory analysis, and robust implementation.

## About You

Essentials

- You have a MSc, PhD or equivalent experience in computational protein engineering, or a closely related field.
- You are a strong programmer, particularly in Python, and are comfortable building scientific software, data pipelines, and analysis tooling rather than relying exclusively on existing tools.
- You have hands-on experience running protein design, protein optimisation, or protein modelling tools and understand their assumptions, outputs, and limitations.
- You are highly proficient at analysing large collections of protein sequences and structures, including clustering, similarity analysis, diversity selection, and visualisation, and can use these analyses to make scientifically informed decisions.
- You can analyse experimental results retrospectively and connect outcomes such as binding, affinity, expression, stability, and developability back to computational predictions and design decisions.
- You have experience with modern protein design and modelling methods such as ProteinMPNN, RFdiffusion, BoltzGen, Boltz, BindCraft or related tools.
- You have strong communication skills

## Nice to Have

- You understand common experimental methods for characterising protein interactions, such as SPR, BLI, ELISA, or FACS, and can interpret their outputs in the context of computational design.
- You have worked with large-scale protein design campaigns, analysing and selecting candidates from thousands to millions of generated sequences or structures.
- You have experience working directly with biotechnology or pharmaceutical partners, translating drug discovery objectives into computational workflows and communicating results to multidisciplinary teams.
- You have contributed to open-source scientific software or published research in protein design, computational biology, structural biology, protein engineering, or biomolecular machine learning.

## What We Offer

- Opportunity to help build the future of AI for biology
- Work alongside world-class researchers in machine learning and molecular modelling
- Direct impact on scientific discoveries and drug discovery programs
- Competitive compensation and significant equity
- Flexible remote working and access to our London office

## About Boltz

## Company Overview
- **One-liner**: Boltz builds foundational AI models and a platform for biomolecular modeling and design, enabling scientists to engineer proteins and small molecules for drug discovery.
- **Entity Type**: Private (Seed stage; raised $28M)
- **Headquarters**: London, United Kingdom (also has an office in Boston, Massachusetts, USA)
- **Founded**: 2025
- **Founders**: Not publicly available (the company originated from research at MIT)

## Core Business
- **Primary industry/industries**: Artificial intelligence for biology and chemistry; biotechnology research
- **Target customers**: B2B – pharmaceutical companies (including all top 20 pharma), biotech startups, academic labs, and individual scientists
- **Mission or purpose statement**: To advance the frontier of AI capabilities in biology through open science and make them universally accessible to every scientist working toward a healthier, more sustainable future. Boltz is a Public Benefit Corporation (PBC).

## Products & Services
- **Boltz-1 / Boltz-1x**: Open-source structure prediction models approaching AlphaFold3-level accuracy; commercially usable under a permissive license.
- **Boltz-2**: Frontier structure prediction model that pushes binding affinity prediction to unprecedented accuracy using large-scale supervision.
- **BoltzGen**: A protein design model and agent capable of generating binders to arbitrary targets, validated across diverse modalities, targets, and assays.
- **Boltz Lab**: A cloud platform (in beta) providing hosted compute, agentic workflows for small-molecule discovery and protein design, collaborative interfaces, and enterprise deployments (multi-tenant, single-tenant, or on-premise). SOC 2 Type 1 verified. Usage-based pricing with generous free tiers.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: $28M in total seed funding (1 prior round)
- **Notable Investors/Partners**: Amplify, a16z, Zetta (co-leads); angel investors include Clement Delangue (CEO of Hugging Face), Factorial Capital, Obvious Ventures. **Key partnership**: multi-year agreement with Pfizer to deploy Boltz Lab across the company and co-develop new foundation models.
- **Growth Signals**: 5M+ downloads, 100k+ scientists using the models, adoption by all top 20 pharma companies and thousands of biotechs. Rapidly expanding team (hiring research engineers, software engineers, product designers, protein engineers).

## Competitive Advantages
- **Open‑source foundation**: Permissively licensed models (Boltz-1, Boltz-1x) that have been validated by the community, lowering the barrier to entry and building trust.
- **Performance and cost**: Claims the lowest price per unit of any major provider in the space; optimized models reduce compute costs.
- **IP protection**: Customers own their outputs, data stays secure, and Boltz does not train on customer data. Offers on-premise deployment for sensitive work.
- **Public Benefit Corporation**: Mission‑aligned structure that explicitly avoids competing with customers (Boltz does not develop drugs itself).

## Strategic Focus
- **Three pillars**: Research (understand and reprogram biology from the bottom up), Product (put powerful AI into scientists’ hands via agentic workflows and eventually autonomous labs), Community (open science and broad accessibility).
- **Current priorities**: Expanding the Boltz Lab platform, fine‑tuning models on proprietary customer data, building agents for new modalities, and scaling enterprise partnerships.

## Why Work Here
- **Culture**: Mission‑driven, open‑science ethos with a strong emphasis on research excellence and product impact. The team is lean (~17 employees as of early 2026) and growing.
- **Remote/Hybrid**: Not explicitly stated; locations include London (HQ) and Boston. Likely flexible given the global team (employees in UK, US, Netherlands, Switzerland).
- **Notable perks**: Opportunity to work on frontier AI models used by 100k+ scientists; direct collaboration with top pharma; usage‑based pricing aligns with customer success; public‑benefit status ensures long‑term mission alignment.
- **Engineering culture**: Heavy focus on research engineering, software engineering, and product design. Looking for protein engineers with preclinical experience to shape the product roadmap.

## Sources
1. [boltz.bio](https://boltz.bio/)
2. [boltz.bio/manifesto](https://boltz.bio/manifesto)
3. [boltz.bio/launch](https://boltz.bio/launch)
4. [linkedin.com/company/boltz-bio](https://linkedin.com/company/boltz-bio)
5. [cbinsights.com/company/boltz](https://www.cbinsights.com/company/boltz)

## Other roles at Boltz

- [Head of Partnerships & Developer Relations](https://feeny.ai/job/head-of-partnerships-developer-relations-boltz-london-081mbxkz1s8j) — London, United Kingdom
- [Head of Community & Growth Marketing](https://feeny.ai/job/head-of-community-growth-marketing-boltz-london-qg7fj0at6fck) — London, United Kingdom
- [Head of Commercial](https://feeny.ai/job/head-of-commercial-boltz-london-ve3f87293d6n) — London, United Kingdom
- [Community Lead](https://feeny.ai/job/community-lead-boltz-london-jgcrvj9gp234) — London, United Kingdom
- [Chief of Staff](https://feeny.ai/job/chief-of-staff-boltz-london-6c3rp0gwc86d) — London, United Kingdom
- [ADME/DMPK Scientist](https://feeny.ai/job/adme-dmpk-scientist-boltz-london-2kbrygkxpkqa) — London, United Kingdom
- [Small Molecule Computational Scientist](https://feeny.ai/job/small-molecule-computational-scientist-boltz-london-j7jz1gjm25xq) — London, United Kingdom
- [Applied ML Engineer/Scientist](https://feeny.ai/job/applied-ml-engineer-scientist-boltz-london-44f5ptd2dtpd) — London, United Kingdom
- [Product Designer](https://feeny.ai/job/product-designer-boltz-london-c47gnt2jtexf) — London, United Kingdom
- [Software Engineer, Product](https://feeny.ai/job/software-engineer-product-boltz-london-ahzffabh70an) — London, United Kingdom