---
title: 'Senior Machine Learning Scientist (Generative Modelling) at relationrx'
canonical: 'https://feeny.ai/job/senior-machine-learning-scientist-generative-modelling-relationrx-london-3zm516qr12hp'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Machine Learning Scientist (Generative Modelling) at relationrx

- **Company:** relationrx
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Posted:** 2026-08-11
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/relationrx/ffd972af-0f46-49ab-bda9-a6c6a0dfdef1/application

**Skills:** Generative modelling, Probabilistic modelling, Representation learning, Neural network architectures, Python, High-performance computing, Machine Learning tooling, Single-cell data analysis, Perturbational datasets experience

> Design and implement generative modelling approaches to learn intervention effects from biological data, focusing on generalisation and experimental design. Collaborate with experimental teams to validate hypotheses and evaluate models for causal coherence and real-world utility in drug discovery.

## Job description

## About Relation

Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.

The opportunity Relation is offering an outstanding opportunity for a Machine Learning Scientist to help build the next generation of generative and predictive models of cellular behaviour. Your work will be central to our mission to understand and control cellular decision-making, enabling novel therapeutic strategies grounded in generative models. You'll be joining a team with access to cutting-edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise. We embrace modern ML tooling, including agentic workflows, to accelerate the pace of research iteration. This is an opportunity to push the boundaries of what generative modelling can achieve in complex, high-dimensional, and noisy real-world systems, and to see your work tested directly in experimental biology.

Day to day, you will

- Design and implement generative modelling approaches that learn intervention effects from diverse biological data, including single-cell perturbation experiments.
- Develop models that go beyond correlation, focusing on generalisation, counterfactual prediction, and experimental design.
- Collaborate with experimental teams to design and validate computational hypotheses via iterative strategies that identify the highest-signal next experiment.
- Evaluate models not just for fit, but for causal coherence, mechanistic fidelity, and utility in guiding real-world interventions.
- Communicate findings clearly to colleagues and stakeholders from different disciplines.

Professionally, you will have

- PhD in ML, statistics, computer science, or a related quantitative field.
- Deep expertise in generative modelling.
- Strong foundations in probabilistic modelling, representation learning, or neural network architectures for structured or sequential data.
- Excellence in Python and familiarity with scalable ML tooling and high-performance computing.
- A disciplined approach to model evaluation, with experience designing experiments that go beyond standard benchmarks to test real-world utility.
- Willingness and ability to engage deeply with biological data; prior experience with single-cell or perturbational datasets is a strong plus.

Bonus experience:

- Track record of impactful publications or open-source contributions in ML.
- Experience working in interdisciplinary teams or applying ML in real-world settings.

Personally, you

- Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
- Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.
- Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.
- Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.
- Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.

Working Style & Culture at Relation At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting!

Recruitment Agencies Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.

## About relationrx

## Company Overview
- **One-liner**: Relation Therapeutics is an end-to-end biotech company using single-cell multi-omics and machine learning to discover and develop transformational medicines for devastating diseases.
- **Entity Type**: Private (Seed/venture-backed; total funding $139M)
- **Headquarters**: London, United Kingdom (with offices in Miami Beach, US, and presence in Italy & India)
- **Founded**: 2019
- **Founders**: Charles Roberts, Benjamin Swerner, and Jake Taylor-King

## Core Business
- **Primary industry**: Biotechnology / Drug Discovery & Development
- **Target customers**: B2B – partnerships with large pharma (Novartis, GSK, Deerfield); ultimately patients for its own pipeline
- **Mission**: “Understand human biology in an unprecedented way; discovering therapies that will treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays and machine learning to drive disease understanding — from cause to cure.”

## Products & Services
- **Lab-in-the-Loop Platform**: An integrated technology stack combining single-cell analysis, genomics, and machine learning to identify druggable targets and develop transformational medicines.
- **Pipeline**: Preclinical/early-stage programs in osteoporosis (first indication announced March 2023) and atopic diseases (strategic collaboration with Novartis announced December 2025). Further undisclosed programs advanced via partnerships with GSK and Deerfield Management.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric**: Total funding of $139M (as of 2026); annual revenue estimated at $1.5M (LinkedIn estimate)
- **Notable Investors/Partners**:
  - DCVC, N Ventures (NVIDIA), Magnetic Ventures, Khosla Ventures, Firstminute Capital, Meltwind, Hitachi Ventures, ARK Invest
  - Strategic partners: Novartis (collaboration on atopic diseases), GSK ($15M equity investment and partnership), Deerfield Management (collaboration to form new companies from targets)
  - Grant from Bill & Melinda Gates Foundation (2020)
- **Growth Signals**:
  - Headcount grew 51.8% YoY to ~97 employees (LinkedIn)
  - Opened new labs in London (opened Feb 2023 by Nobel laureate Sir Paul Nurse)
  - Access to NVIDIA’s CAMBRIDGE-1 supercomputer
  - Multiple new funding rounds: $25M seed (June 2022), $35M seed-2 (March 2024), $15M from Novartis (Dec 2024), $26M further investment (2026)
  - Active job postings: 17 positions (as of mid-2026), with monthly postings up 54.5%

## Competitive Advantages
- **Differentiated platform**: Proprietary “Lab-in-the-Loop” approach that integrates wet-lab single-cell assays with machine learning, enabling high-resolution target discovery directly from patient tissue.
- **Top-tier compute**: Exclusive access to NVIDIA’s most powerful UK supercomputer and deep partnerships with NVIDIA, Mila, and academic leaders.
- **World-class talent**: Scientific advisory board includes Nobel laureate-level researchers and professors from MIT, Stanford, ETH Zurich, and Oxford; team drawn from GSK, BenevolentAI, Wellcome Sanger, and top universities.
- **Pharma validation**: Strong collaboration and equity investments from Novartis, GSK, and Deerfield signal confidence in the platform and pipeline.

## Strategic Focus
- **Priority areas**: Advancing internal pipeline in osteoporosis and atopic diseases; expanding collaborations with pharma to co-develop novel therapeutics; continuing to invest in AI/ML capabilities and single-cell technology.
- **Growth direction**: Scaling the team (especially in machine learning, data science, and biology), forming new spin-out companies with Deerfield, and deepening the use of generative AI for drug design.

## Why Work Here
- **Culture**: Emphasizes collaboration, empowerment, compassionate candor, and a winning attitude. “We set ambitious goals pushing boundaries with a high-performing mindset.”
- **Team**: Highly interdisciplinary – biologists, ML engineers, data scientists, computational chemists, and drug developers working together under one roof.
- **Location**: London HQ with hybrid possibility for some roles; research roles require on-site lab work (lab in King’s Cross area).
- **Perks**: Not publicly detailed, but the company offers the chance to work on cutting-edge AI + biology problems, access to NVIDIA supercomputing, and the impact of bringing new medicines to patients.
- **Engineering/Research Culture**: Strong focus on open collaboration with academia (e.g., Mila, Scripps, Gates Foundation); active hiring for senior ML scientists, computational biologists, and data engineers.

## Sources
1. [relationrx.com](https://www.relationrx.com/)
2. [relationrx.com/careers](https://www.relationrx.com/careers)
3. [relationrx.com/about](https://www.relationrx.com/about)
4. [LinkedIn – Relation Therapeutics](https://uk.linkedin.com/company/relation-therapeutics)
5. [jobs.ashbyhq.com/relationrx](https://jobs.ashbyhq.com/relationrx)

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