Senior AI Scientist

BenevolentAI is seeking to hire a talented AI Scientist to contribute to the development of our industry-leading AI models. At BenevolentAI, we harness the power of artificial intelligence (AI) and human expertise to revolutionise the field of drug discovery. Our unique computational R&D platform, combined with our in‑house pipeline of drug programmes, enables us to develop new and more effective medicines.

As an AI Scientist, you will perform research to develop state‑of‑the‑art solutions around the core problems we work on at BenevolentAI. In particular, you will focus on methods to address crucial challenges in end‑to‑end drug discovery, for example, using multimodal data to identify the best target to modulate in order to treat a disease, or modelling the molecular properties and structures of compounds that can modulate that target.

Responsibilities

• Apply your expertise in machine learning to research new solutions to important problems in drug discovery.
• Work as a member of a cross‑functional team comprising specialists in informatics, engineering, AI and drug discovery to develop new capabilities and improve existing products.
• Keep up‑to‑date with the latest research and progress in machine learning for drug discovery.
• Work with machine learning engineers to help translate research prototypes into practical solutions for BenevolentAI's products and platform.
• Follow robust software development best practices.
• Contribute to writing papers for journals and at conferences.
• Contribute to our thoughtful, collaborative, and ambitious culture.
• Propose novel machine learning projects and research directions that can better address important challenges in drug discovery.
• Promote machine learning best practices, such as: scalable training and deployment, in‑depth model introspection and evaluation, new state‑of‑the‑art methods, and so on.
• Identify opportunities for publications.
• Represent BenevolentAI externally at conferences and events.

Requirements

• An advanced degree (Masters or PhD) in machine learning, computer science, or a related field with a clear focus on empirical research.
• Strong knowledge of modern machine learning methods and techniques (e.g. transformers, LLMs, GNNs, etc.).
• Strong proficiency with Python.
• Knowledge of modern tools for machine learning, including frameworks such as PyTorch.
• Experience building research prototypes and developing product‑worthy tools from them.
• Strong communication skills: ability to communicate complex machine learning concepts to a broad audience.
• Ability to work independently as well as part of a team.
• Bonus points if you have experience applying machine learning in drug discovery or related fields, and/or knowledge of core problems in drug discovery and development.