With over 35 nationalities and a range of backgrounds represented in our Benevolent team, we aim to build an inclusive environment where our people can bring their authentic selves to work, be respected for who they are and the exceptional work they do. We welcome and actively encourage applications from all sections of society and are committed to offering equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, marital, domestic or civil partnership status, sexual orientation, gender identity, parental status, disability, age, citizenship, or any other basis. We see our diversity as an asset as we tackle challenging problems that bridge the gap between drug discovery and technology.
The Machine Learning Engineering team is an interdisciplinary group focused on applying engineering rigour to machine learning problems on the BenevolentAI software platform. To carry out our role, we understand discoveries in machine learning algorithms, as well as the impact of a well-engineered model training and deployment infrastructure with a reliable data pipeline - and innovate on all.
Nice to haves
We share a passion for being part of a mission that matters, and we are always looking for curious and collaborative people who share our values and want to be part of our journey. If that sounds like a fit for you, hit the apply button and join us.
BenevolentAI unites AI with human expertise to discover new and more effective medicines. Our unique computational R&D platform spans every step of the drug discovery process, powering an in-house pipeline of over 25 drug programmes. We advance our mission to reinvent drug discovery by harnessing the power of a diverse team, rich with different backgrounds, experiences, opinions and personalities. In our offices in London and New York and research facility in Cambridge (UK), we work in highly collaborative, multidisciplinary teams, harnessing skills across biology, chemistry, engineering, AI, machine learning, informatics, precision medicine and drug discovery.
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