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Relation Therapeutics

Drug discovery platform using ActiveGraph ML

Associate Director - Platform Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • Significant experience in platform, infrastructure or DevOps engineering, with a strong track record of building and operating complex production environments.
  • Experience leading engineers, formally or informally, with responsibility for significant workstreams from strategy through delivery; setting technical direction, mentoring and developing engineers, and accountability for live production systems.
  • Strong hands-on operational experience, including participation in on-call rotations for production infrastructure, leading responses to significant incidents and driving preventive follow-up changes.
  • Deep expertise in Kubernetes and experience operating infrastructure across hybrid on-premises and cloud environments.
  • Experience building, running or evolving MLOps infrastructure, ideally including notebook environments such as Kubeflow, GPU compute for distributed training and model serving.
  • Familiarity with batch compute for data-intensive scientific workloads and understanding of the reliability, scalability and reproducibility requirements of scientific data pipelines.
  • A track record of maturing CI/CD pipelines, developer tooling and observability across complex, multi-environment platforms.
  • Strong security fundamentals, with hands-on experience designing and implementing appropriate security controls.
  • Excellent written and verbal communication skills, including the ability to co-own strategy with senior stakeholders, challenge decisions constructively and communicate platform strategy to technical and non-technical audiences.
  • Comfort working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
  • Ownership of work, proactively seeking opportunities to contribute and enabling others to do their best work.
  • Technical depth to earn the respect of a highly skilled engineering team, with comfort influencing and contributing at leadership level.
  • Ability to communicate openly and directly, give and receive feedback constructively, and handle challenging conversations respectfully.
  • Ability to seek out diverse perspectives, build strong working relationships and contribute to shared goals across teams.
  • Openness and resilience when embracing challenges, setting high standards and striving to deliver meaningful outcomes.

Responsibilities

  • Partner with the VP of Engineering and peers across Engineering, Data Science and Machine Learning to define and evolve Relation’s platform strategy.
  • Own the architectural strategy for Kubernetes-based clusters and broader hybrid infrastructure, setting technical standards and guardrails for the team to design, build and operate within.
  • Lead and develop the Platform Engineering team, hiring and retaining engineers, setting clear expectations and creating conditions for them to do their best work.
  • Own the scientific compute platform, ensuring it reliably and efficiently meets the evolving needs of Machine Learning and Data Science teams.
  • Drive the maturity of CI/CD pipelines, internal services and developer tooling, treating the platform as a product and internal engineers and computational scientists as its customers.
  • Establish comprehensive observability and robust disaster recovery and failover strategies across on-premises and cloud environments.
  • Own platform security controls, including identity and access management, secrets management, network policy and vulnerability management, ensuring the platform meets the data governance standards required for a clinical-stage biotech working with sensitive patient-derived data.
  • Collaborate across scientific, technical and operational domains, partnering with colleagues across multiple teams and projects and aligning contributions with shared company priorities.

Desired Qualifications

  • Exposure to relevant compliance and governance frameworks, such as ISO 27001, SOC 2 or GDPR, within a research or scientific environment.

About the Company

Relation Therapeutics

Drug discovery platform using ActiveGraph ML

Relation Therapeutics applies machine learning to speed up drug discovery by building a large-scale ActiveGraph ML platform that maps the functional relationships between genes, proteins, and drugs. Its Lab-in-the-Loop approach uses real cells from proprietary biobanks to generate genomic data that continually trains models and prompts new experiments, making target and candidate selection more data-driven. The platform stands apart by applying ActiveGraph ML at scale in drug discovery and by integrating active learning with experimental validation in biology. The goal is to discover therapeutics for currently untreatable diseases and license successful findings to pharmaceutical companies for development and commercialization.

Company size
51-200
Company stage
Late Stage VC
Total funding
$139M
Headquarters
London, United Kingdom
Founded
2019

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