An opportunity is available for an experienced machine learning researcher specializing in generative modeling to join an interdisciplinary team of machine learning specialists, protein engineers, and biologists. The team collaborates to develop transformative approaches to biology and healthcare. This role involves designing innovative generative models aimed at creating functional proteins validated through wet lab assays.
About the Organization
This organization pioneers generative AI models within synthetic biology, focusing on reprogramming biological systems, including advanced gene-editing technologies to address complex genetic diseases. Its mission is driven by a commitment to positively impacting global health through the intersection of artificial intelligence and biology. Founded by an accomplished leader in the field, a former core member of the AlphaFold2 team, the organization is based in London and has secured substantial venture funding from both the UK and the US.
Candidate Profile
Ideal candidates are highly skilled ML researchers with a strong foundation in generative modeling, demonstrated through contributions to prominent open-source libraries, major product launches, or high-impact publications at top conferences. They bring extensive expertise in creating and optimizing machine learning models, combined with robust coding practices, experience in cloud-based ML workflows, and an aptitude for developing scalable ML data pipelines.
Candidates are passionate about optimizing model performance, particularly at the intersection of hardware and deep learning libraries. A mission-driven mindset and relentless curiosity define their approach, enabling them to thrive in dynamic, fast-paced environments and adapt flexibly to evolving methodologies.
Preferred Qualifications
Background in computational biology or protein design, ideally having contributed to ML-driven biological projects
Academic grounding in natural sciences, such as physics, biology, or chemistry
Key Responsibilities
Developing Machine Learning Models (90%):
Curate training and evaluation data, design and refine ML metrics to meet real-world objectives.
Rapidly prototype generative models, analyze advancements, and contribute to shared codebases alongside research scientists, engineers, and protein designers.
Collaborate with the bio team to plan and execute wet lab testing campaigns, adapting model inferences based on experimental feedback.
Support the upkeep of computational and ML development infrastructure.
Continuous Learning and Development (10%):
Stay informed on the latest ML advancements.
Build a solid understanding of protein and cell biology.
Engage in knowledge sharing, present at internal forums, and participate in conferences.
The organization offers a competitive compensation package, comprehensive benefits, and a collaborative work environment that supports hybrid work arrangements. This role is based in London.