About Ignota Labs

Ignota Labs is a multi-award-winning drug turnaround company tackling one of the industry’s biggest bottlenecks: drug safety. Through cutting-edge explainable AI, we identify and resolve toxicity issues in promising drug candidates, unlocking their potential to become safe, effective therapies.

At Ignota Labs, you’ll work at the intersection of cutting-edge AI, real-world drug development and business innovation. Our mission is ambitious, and we’re building a team of equally ambitious, experienced and forward-thinking experts who are excited by the opportunities recent innovation in AI and technology can bring. This is not just relevant for drug development, but also for running the organisation in a more efficient way, allowing experts to automate the small, repetitive tasks and become 10 times more productive.

Ignota Labs are venture capital backed and have recently closed a substantial Seed round with leading Silicon Valley investors.

About the role

As a Research Software Engineer at Ignota Labs, you will design and build the software systems, AI-powered tools, and infrastructure that enable our scientists to rescue failed drugs and bring them safely back to patients. This role spans multiple engineering disciplines, from orchestrating large-scale machine learning workloads, to building agentic systems that accelerate in-licensing, to helping ML researchers deploy state-of-the-art bioinformatics and cheminformatics models. Whether your background is in research engineering, AI application development, or data-driven systems, you can expect to work at the cutting edge of applied technology in drug discovery.

What makes this role unique

Applied: The tools you build will directly enable research that has a tangible path to patient impact.
Multi-disciplinary: You’ll work closely with scientists, ML researchers, and engineers, gaining insight into the end-to-end drug discovery and development process.
Dynamic: Ignota is a fast-paced startup environment — every week will bring new challenges and opportunities to learn.
Innovative:You’ll work with state-of-the-art AI models and systems, deploying them in creative ways to solve complex, real-world R&D problems.

What you’ll do

Design, build, and maintain research software systems and pipelines for bioinformatics, cheminformatics, and related domains.
Orchestrate large-scale ML inference workloads across thousands of models.
Integrate and operationalize large language models and AI services into research workflows.
Collaborate with ML researchers to prototype and deploy experimental models into usable tools.
Build autonomous and agentic systems to streamline literature review, data extraction, and target identification.
Work with scientists to ensure tools are robust, reproducible, and easy to use.
Continuously improve development, testing, and deployment processes for research tools.

Who you are

Mission-oriented: You want your engineering work to accelerate life-changing scientific research.
Biased to action: You thrive in a fast-moving startup and take ownership of delivering results.
Fast learner:You can quickly absorb new technologies, APIs, and scientific concepts.
Collaborative: You work effectively with interdisciplinary teams, adapting your communication for technical and non-technical audiences.
Curious & versatile: You enjoy working across domains — from AI integration to infrastructure — and connecting ideas between them.

What you’ll bring

A strong candidate will have most of the following:

Strong Python development experience, writing production-quality, maintainable code.
Experience integrating and orchestrating AI/LLM services via APIs and related tooling.
Strong technical communication skills.
Ability to rapidly prototype research tools and iterate quickly based on feedback.
Comfort working independently in a fast-paced, high-ambiguity environment.
Familiarity with at least one cloud platform, ideally GCP.

We encourage applicants to apply even if they don’t have all the above, especially if they have some of the following:

Experience in biotech, drug discovery, or pharma R&D workflows.
Familiarity with MLOps tooling, especially Kubeflow or Vertex pipelines.
Experience with DevOps and modern CI/CD pipelines.
Exposure to data science and machine learning workflows, especially in bio/cheminformatics.
Experience with large-scale ML workloads.
Experience building agentic or automation systems for research tasks.

What we offer

A competitive salary (c. £50-70K depending on experience), performance-based bonus, pension and significant equity in a high-growth startup.
Opportunities for rapid career growth and progression.
A collaborative, flexible, hybrid working environment with remote options and tools to support seamless communication.
Vitality health insurance, including mental health, dental, and optical care.
The chance to bring potentially life-saving drugs back to patients - helping improve the lives of millions.

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