---
title: 'Senior Machine Learning Research Engineer at relationrx'
canonical: 'https://feeny.ai/job/senior-machine-learning-research-engineer-relationrx-london-y8h7f6cc1zmc'
type: 'job'
last_seen: '2026-09-04'
---

# Senior Machine Learning Research Engineer at relationrx

- **Company:** relationrx
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Posted:** 2026-08-11
- **Last confirmed live:** 2026-09-04
- **Apply:** https://jobs.ashbyhq.com/relationrx/871060f5-e968-4c3d-92a7-33293fa88a1e

## 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 Senior Machine Learning Research Engineer to help build and scale the next generation of generative and predictive models of cellular behaviour. Research Engineers at Relation are software engineers with a deep understanding of machine learning and deep learning, acting as a critical bridge between theory and implementation: designing, building, and scaling the complex systems on which our ML research depends. You'll be joining a team with access to cutting-edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise, and a culture that embraces modern ML tooling, including agentic workflows. Key responsibilities include implementing and optimising large neural network models; building robust infrastructure for distributed training, evaluation, and inference; and partnering with ML Scientists to take research from prototype to production-grade systems applied to large, multi-modal biological data, tested directly in experimental biology.

## DAY TO DAY, YOU WILL

- Implement and optimise large models, partnering with ML Scientists to translate research ideas into reproducible, scalable training pipelines.
- Profile and optimise training across compute, memory, and I/O, pursuing measurable gains in throughput, convergence, and stability.
- Design and implement distributed training strategies across multi-GPU and multi-node configurations.
- Build and maintain core ML infrastructure.
- Contribute to architectural and algorithmic decisions, bringing engineering judgment into research discussions.
- Optimise inference and downstream deployment so models can be used by data scientists and biologists in our discovery workflows.
- Address numerical, performance, and reliability issues across the stack.
- Establish and maintain engineering practices in research code.
- Track developments in ML systems and bring relevant advances into our stack.

## PROFESSIONALLY, YOU WILL HAVE

- A degree in Computer Science, Engineering, Physics, or a related quantitative discipline; industry experience as an ML / research engineer working on large neural network training.
- Strong software engineering fundamentals in Python and deep expertise in PyTorch (or equivalent modern ML frameworks).
- Hands-on experience training large neural networks at scale, including distributed training frameworks.
- Demonstrable experience profiling and optimising GPU workloads.
- Working knowledge of cloud-based ML infrastructure and containerised environments.
- A track record of taking research code from prototype to robust, reusable infrastructure that other people actually use.

Bonus experience:

- CUDA / Triton kernel development; FlashAttention-style attention implementations; experience with foundation models for biology, vision, or language; contributions to open-source ML frameworks.

## 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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- [Director, Clinical Pharmacology](https://feeny.ai/job/director-clinical-pharmacology-relationrx-london-wpw6zyh37q45) — London, United Kingdom
- [Associate Director, Platform Engineering](https://feeny.ai/job/associate-director-platform-engineering-relationrx-london-extzcz2yecwc) — London, United Kingdom
- [Machine Learning Scientist – Sequence Modelling](https://feeny.ai/job/machine-learning-scientist-sequence-modelling-relationrx-london-cytz3vj63gxw) — London, United Kingdom
- [Senior Machine Learning Scientist (Single Cell)](https://feeny.ai/job/senior-machine-learning-scientist-single-cell-relationrx-london-kna3qrjnfad0) — London, United Kingdom
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- [Senior Machine Learning Scientist (Generative Modelling)](https://feeny.ai/job/senior-machine-learning-scientist-generative-modelling-relationrx-london-3zm516qr12hp) — London, United Kingdom
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