Senior AI Scientist, BenevolentAI

Salary not provided
Python
PyTorch
Senior level
London
BenevolentAI

AI-drug discovery

Open for applications

BenevolentAI

AI-drug discovery

201-500 employees

HealthcareB2BArtificial IntelligenceEnterpriseBiologyMachine LearningScience

Open for applications

Salary not provided
Python
PyTorch
Senior level
London

201-500 employees

HealthcareB2BArtificial IntelligenceEnterpriseBiologyMachine LearningScience

Company mission

BenevolentAI's mission is to unlock the power of AI to transform drug discovery and bring effective medicines to every patient. Their vision is to drive transformational change through scalable technology solutions that result in a consistent pipeline of successful trials and new medicines for patients.

Role

Who you are

  • 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

What the job involves

  • BenevolentAI is seeking to hire a talented AI Scientist to contribute to the development of our industry-leading AI models
  • 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
  • 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

Salary benchmarks

Our take

There is a lot of research being done in the pharmaceutical industry. BenevolentAI say there's a new research paper being published every 30 seconds. They argue this information is not being used in a smart way for the discovery and development of new drugs.

To tackle this problem, BenevolentAI uses artificial intelligence to analyse biomedical information, from clinical trials data to academic papers. They can then identify molecules that have failed in clinical trials and predict how these same compounds can instead be more efficient targeting other diseases.

They argue this approach can dramatically accelerate the discovery of new drugs. They've collaborated with large pharma companies like AstraZeneca and Johnson & Johnson subsidiary Janssen Pharmaceutica. A SPAC merger of 1.5 billion euros included AstraZeneca as an investor and will help BenevolentAI accelerate product development.

It's a big market, with Global Market Insights estimating the global healthcare AI market will exceed $10 billion by 2024. This gives them a big opportunity, but it won't be an easy problem to tackle.

Steph headshot

Steph

Company Specialist at Welcome to the Jungle

Insights

Top investors

Some candidates hear
back within 2 weeks

51% female employees

15% employee growth in 12 months

Company

Funding (last 2 of 3 rounds)

Sep 2019

$90m

LATE VC

Apr 2018

$115m

LATE VC

Total funding: $305m

Company benefits

  • Work from home opportunities

Company values

  • Put patients first: Everything we do is geared to getting the right medicine to the right patient, faster
  • Break boundaries: We deliberately cross traditional boundaries between technology and science, human and machine, to create unique approaches
  • Own the solution: We never hold back from contributing our point of view and taking responsibility
  • Drive to delivery: We use data to drive decision-making and deliver with the right level of validation

Company HQ

Fitzrovia, London, UK

Leadership

Joanna Shields

(CEO, not founder)

Long career in technology, having previously worked at Google, Facebook and Bebo. Appointed to the House of Lords in 2014 and works as a Digital Economy Adviser to the UK Government.

Michael Brennan

(Co-founder & Non-Executive Director)

Previously Head of Corporate Development at BenevolentAI. Before cofounding the company, they were Head of Corporate Development at Proximagen Group and Chief Executive of Novum Securities.

Ivan Griffin

(Co-founder & COO)

Worked as a Venture Capitalist for over a decade. Also helped launch Genomics England Ltd, a Company created to deliver the 100,000 Genomes Project as launched by the Prime Minister in 2013. Holds a D.Phil. in Cognitive Neuroscience from the University of Oxford where they also completed a year’s post-doctoral research.


People progressing

Joined as a Biomedical Informatics Manager. Promoted to VP after 10 months, then again to SVP of Informatics and Data.

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