Software Engineer (Applied ML Research Engineering), London

June 29

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Isomorphic Labs

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We are reimagining the entire drug discovery process from first principles with an AI-first approach.

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Description

• This is an exciting opportunity for you to work on a greenfield ML-based software platform that will transform the biopharmaceutical world as we know it. • Working in a highly creative, iterative environment, you will be partnering with leading engineers, scientists and ML researchers to build the critical platform driving that transformation. • Partner with the ML Research, Drug Design, and Data Engineering teams to design, develop, train, and evaluate a variety of cutting edge ML models at unprecedented scale. • Apply the state-of-the-art ML models and techniques to real-life drug discovery challenges. • Build a world-class ML drug design research environment with scalable software and libraries. • Create novel instrumental drug discovery tools in partnership with domain experts. Take end-to-end ownership from rapid prototyping to production-quality code. • Iterate collaboratively with scientists and domain experts to deeply understand feature requirements and user feedback. • Develop tools and libraries to enable large-scale machine learning experiments across thousands of accelerators. • Maximise model performance, scalability, and robustness for production use within our computational platform.

Requirements

• Deep experience with developing large-scale machine learning models. • Significant experience with solving real-life challenges with ML models and techniques. • Experience with modern ML frameworks including at least one of JAX, PyTorch or TensorFlow. • Experience with the full ML research and development lifecycle. • Experience partnering with research and product teams to prototype and ideally productionise ML models. • Strong software engineering experience with software design / architecture skills. • Extensive programming experience using any mainstream programming languages, including strong Python experience. • Strong understanding of ML theory and applications. • Strong understanding of data structures and algorithms. • Either a Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.