Associate Director, Platform Engineering

Hlx Life Sciences; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Hlx Life Sciences seeks an Associate Director of Platform Engineering to lead a team responsible for hybrid compute infrastructure, developer platforms, and scientific compute environments powering ML, data science, and computational research.

You will set the direction across on‑prem and cloud, define standards, and build the team to deliver a resilient, scalable platform for notebooks, model training, serving, and data pipelines.

Qualifications

• Significant experience in Life sciences industry functioning as platform, infrastructure, or DevOps engineering, with a strong track record of building and operating complex production environments.
• Experience leading engineers, either formally or informally, with responsibility for significant workstreams from strategy through to delivery.
• A track record of setting technical direction, mentoring and developing engineers, and taking 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 implementing improvements to prevent recurrence.
• Deep expertise in Kubernetes, alongside 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, with an 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.

Responsibilities

• Partner with the VP of Engineering and peers across Engineering, Data Science, and Machine Learning to define and evolve the platform strategy.
• Own the architectural strategy for Kubernetes-based clusters and broader hybrid infrastructure, setting the technical standards and guardrails within which the team designs, builds, and operates.
• Lead and develop the Platform Engineering team, hiring and retaining exceptional engineers, setting clear expectations, and creating the 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.

Skills

Kubernetes

Platform engineering

CI/CD pipelines

Observability

Security fundamentals

Cloud & on-prem infrastructure

Kubeflow

Tools

Kubeflow

Job description

Location: London- x3 days onsite per week

Employment Type: Full-time

The Opportunity

As Associate Director, Platform Engineering, you will lead the team responsible for hybrid compute infrastructure, developer platforms, and scientific compute environments that power machine learning, data science, and computational research.

Reporting to the VP of Engineering, you will work closely with your team and senior stakeholders across Engineering, Data Science, and Machine Learning to define and evolve the organisation's platform strategy.

The platform spans on-premises infrastructure and public cloud environments, supporting computational scientist notebooks, model training and serving, internal services, and large-scale data and scientific pipelines.

You will set the technical direction across these areas, build and develop the team responsible for delivering them, and ensure the platform continues to evolve alongside the needs of the organisation.

Day to Day, You Will

• Partner with the VP of Engineering and peers across Engineering, Data Science, and Machine Learning to define and evolve the platform strategy.
• Own the architectural strategy for Kubernetes-based clusters and broader hybrid infrastructure, setting the technical standards and guardrails within which the team designs, builds, and operates.
• Lead and develop the Platform Engineering team, hiring and retaining exceptional engineers, setting clear expectations, and creating the 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 IAM, secrets management, network policy, and vulnerability management.
• Ensure the platform meets appropriate data governance and security standards when working with sensitive data.

Professional Experience:

• Significant experience in Life sciences industry functioning as platform, infrastructure, or DevOps engineering, with a strong track record of building and operating complex production environments.
• Experience leading engineers, either formally or informally, with responsibility for significant workstreams from strategy through to delivery.
• A track record of setting technical direction, mentoring and developing engineers, and taking 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 implementing improvements to prevent recurrence.
• Deep expertise in Kubernetes, alongside 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, with an 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, with the ability to co-own strategy with senior stakeholders, challenge decisions constructively, and communicate platform strategy clearly to both technical and non-technical audiences.

Working Style & Culture

The organisation operates in a matrixed, interdisciplinary environment where impact is driven through collaboration across scientific, technical, and operational domains.

You will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared organisational priorities.

Collaboration, ownership, technical excellence, and a strong focus on delivering meaningful outcomes are central to the working environment.