Software Engineer (ML Infrastructure), 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.

This is an exciting opportunity for a small number of innovative and versatile software engineers to work in a fast-paced and research-centric environment. 

You will collaborate extensively with internal engineering and research teams to evolve the foundational infrastructure that makes it easy to train and deploy novel machine learning models over vast (and growing) pools of compute and data.

For this role we are looking for individuals with experience of designing and evolving complex systems at significant scale. Domain knowledge of ML inference, training or research infrastructure will be a strong advantage, though we encourage applications from candidates with a record of exceptional impact in any field.

• →Evolve the ML infrastructure platform to accelerate both human and agent-driven research at scale
• →Explore options to deploy agents to increase the robustness and reliability of the platform
• →Develop the platform to enable the next generation of distributed, performance-critical training and inference workloads 
• →Partner closely with engineering, research and product teams to identify and deliver impact

• Demonstrated ability to independently identify opportunities, deliver solutions and work effectively in cross-functional teams
• Experience building and evolving infrastructure or platforms at significant scale
• Strong Python programming (though familiarity with any particular library is not required)

• Domain knowledge of ML inference, training or research infrastructure
• Strong hands-on experience building for Kubernetes
• Experience providing platforms to internal customers
• Experience with Google Cloud Platform (GCP)
• Experience with multi-cloud environments

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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