Senior AI Researcher

4 weeks ago


London, Greater London, United Kingdom BenevolentAI Full time

About the Role

BenevolentAI is seeking to hire a talented AI Scientist to contribute to the development of our industry-leading AI models. Our unique computational R&D platform, combined with our in-house pipeline of drug programmes, enables us to develop new and more effective medicines. With offices in London and a state-of-the-art research facility in Cambridge (UK), we have cultivated a diverse team of professionals from various scientific, technological, and business backgrounds.

As an AI Scientist, you will perform research to develop state-of-the-art solutions around the core problems we work on at BenevolentAI. You will focus on methods to address crucial challenges in end-to-end drug discovery, including multimodal data analysis and molecular property modeling.

Responsibilities

  • Apply your expertise in machine learning to research new solutions to important problems in drug discovery. You will collaborate with cross-functional teams to develop new capabilities and improve existing products.
  • Stay up-to-date with the latest research and progress in machine learning for drug discovery.
  • Work with machine learning engineers to 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.

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.
  • 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.


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