Bioinformatics Engineer, London

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed.

Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases.

We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.

Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.

You will collaborate to build a high-fidelity biological data layer that serves as the foundation for machine learning at Isomorphic Labs. Moving beyond raw data ingestion to create curated biological datasets, you will ensure model training is consistently grounded in high-quality, standardized, and version-controlled biological data. Harmonizing disparate public datasets and internal data into a coherent representation, you will unlock the information needed to fuel our mission to solve all disease.

Working in an interdisciplinary environment, you will partner with ML Research, Computational Biology, Drug Development, and Chemistry teams to drive the adoption of standardized bioinformatics primitives and best practices into their daily workflows. Your work will provide projects with a significant head start by solving complex bioinformatics problems at the platform level. Ultimately, your contribution ensures that our models are built on a robust and integrated data resource, producing predictions on a coherent view of biology, directly accelerating our Drug Discovery programs.

• →Develop and operate large-scale bioinformatics pipelines for high-throughput data analysis, ensuring reliable processing from raw data (e.g., FASTQ, BAM, mzXML) to ML-ready datasets.
• →Apply bioinformatics best practices to the ingestion and harmonization of complex datasets, ensuring model training is grounded in high-quality, version-controlled biological data, and coherently integrated datasets.
• →Harmonise disparate public databases (e.g., Ensembl, UniProt, Reactome, Open Targets), implementing rigorous versioning and mapping strategies to mitigate identifier collisions, data loss, and semantic drift across releases.
• →Act as a strategic partner to our ML Research, Computational Biology, Drug Development, and Chemistry teams, championing the adoption of the internal bioinformatics platform and standardized biological data primitives into their daily research workflows.
• →Participate in research projects as a "Deployed Engineer", providing customised solutions, and identifying technical gaps, while ensuring project-specific insights are contributed back into the core bioinformatics platform.
• →Provide documentation, guidance, and training on data resources and curation processes to the wider organization.

• Proven experience with the large-scale processing of raw bioinformatics data (e.g., FASTQ, BAM, mzXML).
• A demonstrable track record of delivering high-quality bioinformatics outputs across varied modalities (e.g., genomics, proteomics, functional genomics, systems biology, single cell).
• Experience delivering bioinformatics solutions directly to research teams, scientific communities, or industry projects, with a strong focus on user enablement.
• Experience writing production-grade code in Python and developing automated, scalable bioinformatics pipelines.
• PhD or MSc in Bioinformatics, Computational Biology, or a related field, or equivalent practical experience in a biopharmaceutical or research environment.

• Experience with domain-specific workflow systems (e.g., Nextflow) for scaling high-throughput pipeline execution.
• Familiarity with general-purpose data orchestration and processing frameworks (e.g., Dagster, Apache Beam) for integrating research pipelines into a production platform
• Familiarity with building and maintaining bioinformatics infrastructure on Google Cloud Platform (GCP).
• Familiarity with modern, high-performance DataFrame libraries (e.g., Polars), and relational data modeling and analysis (SQL).
• Exposure to machine learning concepts and the specific data requirements for training ML models.
• Demonstrable experience working with regulated PHI data.
• Extensive experience in software development with Python.

We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it. 

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