Bioinformatics Applied AI Engineer
Hybrid London Full-time Mid-level AI Engineering
At a glance
Mid-level AI Engineering role at Bactobio. London · full-time · no salary stated · we estimate £77,500–£137,500.
Estimated pay
Bactobio has not published a salary for this role. The figure below is our estimate, not theirs.
£77,500 – £137,500
What the middle half of mid-level AI engineering roles in London paid, among postings that did state a salary.
Worked out from 7 postings that stated pay, median £90,000. Last updated Oct 22, 2026.
RoleAI Engineering
SeniorityMid-level
LocationLondon
WorkplaceHybrid
EmploymentFull-time
PostedSep 11, 2026 · 5w ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Translate uncertain questions from lab scientists into scoped work with explicit measures of success
- Build linked, multi-stage LLM processes that examine biology records and knowledge graphs, then offer explainable recommendations
- Set up benchmarking systems and prepare datasets to assess the workflows
- Track new model capabilities, adjusting prompts, tool choices and orchestration, and help ship workflows through the software platform
What you bring
- A quantitative master's or PhD with a substantial ML/AI focus, or two years in an industry ML/AI role
- Strong knowledge of LLMs, including tool use and assessment, alongside knowledge graphs and multimodal data
- Experience with omics and experimental records, plus Python skills and substantial use of modern ML and data-science tools
Who this fits
This hands-on role suits someone interested in both AI and biology who wants code to support real experiments and scientific decisions. You’ll work with wet-lab scientists and teams across disciplines. The position is based in London and is hybrid.
From the employer
We are looking for a Bioinformatics Applied AI Engineer to build AI-powered workflows that drive insight in bioinformatics and metabolomic chemistry.
Company
Bactobio is a London biotech startup. We work to solve the antimicrobial resistance crisis across healthcare and agriculture by producing the next generation of market-leading antimicrobials. Since inception in 2020, Bactobio has built a deep-tech platform that combines AI, synthetic biology, and multiomics to routinely discover new antimicrobial classes from nature. Our antimicrobial platform is fully operational. We use it to build portfolios of new, safe, and effective antimicrobial classes that bypass resistance, aimed at the most serious diseases, and move them towards commercialisation.
Our culture is built around impact, empowerment, and collaboration. We attract incredible scientists from world-leading institutions, mix them with operational experts, and provide guidance through industry leaders acting as mentors. We strongly believe that diversity combined with open and inclusive conversations leads to better solutions. As a result, we have created a collaborative work environment, where ambitious people enjoy working together to make the world greener and safer.
Role
This role lies at the heart of our discovery engine. You’ll design and build LLM workflows that support decision-making in bioinformatics and metabolomic chemistry at Bactobio, using the latest capabilities in modern AI.
You'll turn messy scientific questions and trade-offs into recommendations scientists can use and trust, working in Python with frontier models and our proprietary biological data.
This is an applied role that ships code. We love to explore, but our goal is always something that runs, gets used, and moves the platform forward.
You'll thrive here if you care about AI and biology in equal measure and want your work tied to real experiments, real decisions, and real outcomes. Gaps are yours to fill, ideas are yours to try, and being wrong now and then is part of the work. You won't be a cog in the machine; you'll be a creative voice with room to use it.
Team
You’ll be joining a vibrant, tight-knit, and highly collaborative company of about fifty people. We sit together and take genuine interest in one another's work. Your home will be the Bioinformatics & Machine Learning team, but day to day you’ll work with microbiologists, chemists, automation and software engineers, and the business development team, with a front-row seat to the strategic and commercial decisions that shape the company.
Everyone who writes code at Bactobio contributes to a single shared codebase. We care about well-designed data models, best practices with sensible implementations, and building a tech stack that’s productive, maintainable, and genuinely enjoyable to work in.
Company
Bactobio is a London biotech startup. We work to solve the antimicrobial resistance crisis across healthcare and agriculture by producing the next generation of market-leading antimicrobials. Since inception in 2020, Bactobio has built a deep-tech platform that combines AI, synthetic biology, and multiomics to routinely discover new antimicrobial classes from nature. Our antimicrobial platform is fully operational. We use it to build portfolios of new, safe, and effective antimicrobial classes that bypass resistance, aimed at the most serious diseases, and move them towards commercialisation.
Our culture is built around impact, empowerment, and collaboration. We attract incredible scientists from world-leading institutions, mix them with operational experts, and provide guidance through industry leaders acting as mentors. We strongly believe that diversity combined with open and inclusive conversations leads to better solutions. As a result, we have created a collaborative work environment, where ambitious people enjoy working together to make the world greener and safer.
Role
This role lies at the heart of our discovery engine. You’ll design and build LLM workflows that support decision-making in bioinformatics and metabolomic chemistry at Bactobio, using the latest capabilities in modern AI.
You'll turn messy scientific questions and trade-offs into recommendations scientists can use and trust, working in Python with frontier models and our proprietary biological data.
This is an applied role that ships code. We love to explore, but our goal is always something that runs, gets used, and moves the platform forward.
You'll thrive here if you care about AI and biology in equal measure and want your work tied to real experiments, real decisions, and real outcomes. Gaps are yours to fill, ideas are yours to try, and being wrong now and then is part of the work. You won't be a cog in the machine; you'll be a creative voice with room to use it.
Team
You’ll be joining a vibrant, tight-knit, and highly collaborative company of about fifty people. We sit together and take genuine interest in one another's work. Your home will be the Bioinformatics & Machine Learning team, but day to day you’ll work with microbiologists, chemists, automation and software engineers, and the business development team, with a front-row seat to the strategic and commercial decisions that shape the company.
Everyone who writes code at Bactobio contributes to a single shared codebase. We care about well-designed data models, best practices with sensible implementations, and building a tech stack that’s productive, maintainable, and genuinely enjoyable to work in.
- Collaborate daily with wet-lab scientists to turn ambiguous scientific decisions into well-specified tasks with clear success criteria.
- Design and build multi-step LLM workflows that query biological data and knowledge graphs and produce recommendations with traceable reasoning.
- Build benchmarking infrastructure and curate evaluation datasets.
- Keep up with frontier model capabilities, and iterate on models, prompts, tool design, and orchestration.
- Contribute to our software platform, especially data architecture, pipelines, and model/workflow deployment.
- A Master's or PhD in a quantitative field with a significant ML/AI component, or at least two years of ML/AI-focused industry experience.
- Strong understanding of LLMs (including tool use and evaluation), knowledge graphs, and multimodal data.
- Comfort working with biological data (omics and experimental metadata) and collaborating with domain experts.
- Proficiency in Python, with substantial experience in modern ML and data science tooling.
- A research or industry track record applying ML in biotech or adjacent scientific settings.
- Experience shipping production code in a shared codebase.