Machine Learning Engineer, Healx
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Drug discovery for rare diseases
Open for applications
Drug discovery for rare diseases
101-200 employees
Open for applications
+ Share options
101-200 employees
Company mission
Healx's mission is to pioneer the next generation of drug discovery in order to bring novel, effective treatments to rare disease patients around the world.
Role
Who you are
- We encourage you to provide a covering letter to explain why you think you'd be successful in this role
- You have 2-5 years professional (in academia or industry) experience in machine learning, artificial intelligence or related field
- You are excited about taking on new challenges and responsibilities in a mission-driven startup aiming at improving patient outcomes
- You have an advanced degree (masters, PhD) in machine learning, biochemistry or related field with a focus on applied research or equivalent industry experience applying machine learning to complex real-world problems
- You have a strong software development experience in Python and a good appreciation of the principles of software engineering
- You thrive in a highly cross-functional environment and you appreciate the opportunity to step up and leave your mark by taking ownership of meaningful technical challenges, contributing ideas that shape the direction of our platform and driving solutions from concept through to deployment
- You are able to work independently to scope, plan and deliver end-to-end machine learning solutions, managing your own priorities effectively and communicating progress and blockers proactively
- You are comfortable navigating a degree of ambiguity, making pragmatic decisions when needed, and you know when to seek input from the broader team to ensure quality and alignment
What the job involves
- Healx is looking for a talented Machine Learning Engineer to join our Tech team to help develop our drug discovery platform and discover new treatments for rare diseases
- This role will report to our Director of Tech Strategy and will contribute to developing and applying cutting edge machine learning approaches, knowledge graph reasoning and agentic workflows that underpin our Drug Discovery workflows to find novel treatments for rare diseases
- You will be part of a highly cross-functional and collaborative team that brings together machine learning engineers, software engineers, bioinformaticians and drug discovery scientists
- You will work closely with domain experts to translate complex biological questions into robust, scalable machine learning solutions, and your work will have a direct and meaningful impact on our drug discovery programmes
- Build automated reasoning over large knowledge graphs and proprietary methods for efficient generation of experimentally testable therapeutic hypotheses
- Contribute to building, maintaining and improving our rare-disease knowledge graphs used to identify and reason over novel therapeutic hypotheses
- Develop agentic tools and workflows to enable our teams to unlock insight from proprietary data and large datasets
- Contribute and advocate for best engineering practices across our tech teams
- What success will look like in 6 months
- You’ve built a strong understanding of Healx’s drug discovery workflows, our rare-disease knowledge graphs and the key users of our platform
- You’ve delivered at least one meaningful improvement to our knowledge graph reasoning or hypothesis-generation stack (from prototype through to production), with appropriate evaluation, testing and documentation
- You’re operating effectively in our hybrid, cross-functional environment—communicating progress and trade-offs clearly, partnering well with scientists and engineers, and demonstrating ownership from discovery through delivery
- You’re consistently applying and advocating for strong engineering practices (e.g., code quality, reviews, reproducibility, experiment tracking, monitoring/observability where relevant), helping raise the bar across the team
Our take
There are 7,000 known rare diseases around the world, and only 5% of them have an approved treatment. Healx solves this problem by leveraging AI to develop and identify drug treatments for rare conditions.
Healx's platform, Healnet, uses machine learning to find connections between rare diseases and existing drugs. Repurposing drugs is more time and cost effective than developing new treatments, and therefore has broad appeal within the pharma community.
With substantial funding awarded in 2024, HealX is focusing on supporting clinical trials and expanding its US presence. Trials within the US are expected to yield results in 2026, marking an exciting time of growth for the company.
Freddie
Company Specialist at Welcome to the Jungle
Insights
58% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Aug 2024
$47m
SERIES C
Nov 2023
$22m
LATE VC
Total funding: $137m
Company benefits
- Share options
- Remote and flexible working
- Enhanced parental leave
- Quarterly socials
- Private medical insurance
- Life insurance
- Generous pension contributions
Company HQ
Cambridge, UK
Leadership
Dr Tim Guilliams
(Co-Founder & CEO)Previously worked as a Junior Associate Fellow at the Centre for Science and Policy. Is Founding Director and Trustee of Cambridge Rare Disease Network, and an Entrepreneurship Fellow at Cambridge Judge Business School.
David Brown
(Co-Founder & Non-Exec Board Member)Previously served as Managing Director of Alchemy Biomedical Consulting. Is Chair of the Board at ProFactor Pharma and Babraham Institute Enterprise.
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