Senior Staff MLOps Engineer

Boehringer Ingelheim; Greater London; Hybrid; GBP 120,000 - 170,000; Full time

Benefits offered by this job

Top Employer recognition in UK

Job summary

Boehringer Ingelheim, London, seeks a senior MLOps leader to own the architecture, standards and technical direction for the AI Accelerator. You will ensure models move efficiently from experimentation to reliable production deployment, defining tooling, platforms and engineering practices for scalable model training, monitoring and governance.

This role blends strategic leadership with hands-on execution, reporting to the AI Enablement leadership team and collaborating with the Senior Staff

Qualifications

• PhD or MSc in a STEM subject (or equivalent).
• Extensive senior staff experience in MLOps/ML Platform Engineering or ML Engineering with mentoring responsibility.
• Deep MLOps lifecycle expertise: training orchestration, experiment tracking, model registries, CI/CD, deployment and monitoring.
• Strong Python proficiency and experience building scalable production platforms with Docker/Kubernetes/Helm.
• Strong collaboration and influencing skills across research, engineering and business.

Responsibilities

• Own the MLOps architecture and roadmap for the AI Accelerator, defining the end-to-end model lifecycle (training orchestration, experiment tracking, registries, CI/CD, deployment and monitoring).
• Establish MLOps standards and engineering practices, including testing, containerisation, deployment patterns, packaging, release management and production operations.
• Govern model artefacts: versioning, lineage, configuration control for weights, parameters and hyperparameters.
• Enable large-scale distributed training and federated learning with AI Infrastructure for scalable research-to-production velocity.
• Drive efficiency and cost optimisation across training and inference workloads in enterprise infrastructure.
• Coach and mentor MLOps engineers, onboarding and leading the team as it grows, serving as senior escalation point.

Skills

MLOps

ML Platform Engineering

Machine Learning Engineering

Python

Team collaboration

Mentoring engineers

Education

PhD or MSc in STEM

Tools

Docker

Kubernetes

Helm

Job description

Most diseases are still poorly understood at a biological level. Despite decades of research, the causal mechanisms driving many conditions remain unclear, limiting our ability to identify the right targets, design the right interventions and bring the right medicines to patients.

The AI Accelerator exists to change that. Based in London and sitting within Computational Innovation (@computationalinnovation), a global organisation spanning computational biology, human genetics, data excellence and AI, the Accelerator's mission is to build production-quality AI capabilities that deepen our understanding of disease biology and increase probability of success.

We do this by applying neural-based methods across the biomedical data landscape to integrate heterogeneous, multimodal data sources, infer biological relationships and embed causal thinking into what we build. The goal is not just to predict but to explain and understand why disease occurs.

It could be electronic health records and medical imaging to support patient segmentation. It could be 'omics data to identify novel therapeutic targets. It could be predicting transcriptional change for a given disease-causing variant. It could be simulating the effect of modulating a target of interest.

Breakthrough AI research only creates value when it can be reproduced, scaled, deployed and trusted. MLOpssits at the heart of that challenge. The AI Accelerator's ability to train biomedical foundation models, manage experimentation at scale, operationalise discoveries and deliver production-quality AI depends on the ML platform, tooling and practices that underpin the entire model lifecycle.

AI ACCELERATOR

Most diseases are still poorly understood at a biological level. Despite decades of research, the causal mechanisms driving many conditions remain unclear, limiting our ability to identify the right targets, design the right interventions and bring the right medicines to patients.

The AI Accelerator exists to change that. Based in London and sitting within Computational Innovation (@computationalinnovation), a global organisation spanning computational biology, human genetics, data excellence and AI, the Accelerator's mission is to build production-quality AI capabilities that deepen our understanding of disease biology and increase probability of success.

We do this by applying neural-based methods across the biomedical data landscape to integrate heterogeneous, multimodal data sources, infer biological relationships and embed causal thinking into what we build. The goal is not just to predict but to explain and understand why disease occurs.

It could be electronic health records and medical imaging to support patient segmentation. It could be 'omics data to identify novel therapeutic targets. It could be predicting transcriptional change for a given disease-causing variant. It could be simulating the effect of modulating a target of interest.

Breakthrough AI research only creates value when it can be reproduced, scaled, deployed and trusted. MLOpssits at the heart of that challenge. The AI Accelerator's ability to train biomedical foundation models, manage experimentation at scale, operationalise discoveries and deliver production-quality AI depends on the ML platform, tooling and practices that underpin the entire model lifecycle.

THE POSITION

We are seeking a senior leader inMLOpsEngineering to join Computational Innovation's AI Accelerator (@computationalinnovation). In this role, you will own the MLOps architecture, standards and technical direction for the AI Accelerator, ensuring that models can move efficiently from experimentation to reliable production deployment and support. You will define the tooling, platforms and engineering practices that enable large-scale model training, experiment tracking, deployment, monitoring and governance.

This is both a strategic and hands‑on technical leadership role. You will define architecture and standards, help solve the most challenging ML platform problems yourself and serve as the senior technical authority for MLOps within the AI Accelerator. As a senior member of the AI Enablement leadership team, you will help shape the direction of the function alongside the Senior Staff Data Engineer and Senior Staff AI Infrastructure Engineer.

This is a unique opportunity to be part of a critical strategic initiative for a pharmaceutical company that invests heavily in research and development to discover and develop innovative therapies that can improve and extend lives in areas of high unmet medical need.

This is a hybrid role with approximately 4 days a week in the office.

Key Responsibilities

• Own theMLOpsarchitecture and roadmap for the AI Accelerator, defining and evolving the end-to-end model lifecycle, including training orchestration, experiment tracking, model registries, CI/CD, deployment and monitoring.
• EstablishMLOpsstandards and engineering practices, including model testing and validation, containerisation, deployment patterns, model packaging, release management and production operations.
• Establish standards for model artefact management, versioning, lineage and configuration control, ensuring model weights, parameters, hyperparameters and model cards are appropriately governed and traceable.
• Enable large‑scale distributed training and, where appropriate, federated learning approaches, working closely with AI Infrastructure to provide scalable, efficient model‑training capabilities and enable research to production velocity.
• Drive efficiency and cost optimisation across training and inference workloads, ensuring the AI Accelerator makes effective use of enterprise infrastructure.
• Establish ways of working and coach other team members, onboarding, mentoring and technically leading MLOps engineers as the team grows, while acting as the senior escalation point for complex MLOps challenges.

Requirements

• PhD orMSc and equivalent experience in a STEM subject.
• Extensive experience operating atsenior stafflevel within anMLOps, ML Platform Engineering or Machine Learning Engineering function with a proven track record of defining technical strategy, architecture and engineering standards for ML platforms and production AI systems, and with experience mentoring engineers and establishing engineering principles.
• Deep expertise across theMLOpslifecycle, including training orchestration, experiment tracking, model registries, CI/CD for machine learning, deployment, serving and monitoring of AI systems in production.
• Strong software engineering skills, includingproficiency in Python, and experience building scalable production-grade platforms and tooling, along with a deep understanding of containerisation and orchestration technologies such as Docker, Kubernetes and Helm.
• Strong collaboration and influencing skills, with the ability to work effectively across research, engineering and business teams.

WHY THIS IS A GREAT PLACE TO WORK

Boehringer Ingelheim has been recognised as a Top Employer in the UK, demonstrating our commitment to building an exceptional workplace through strong people practices and supportive HR policies.

To learn more about why BI is a great place to work, visit:

https://www.boehringer-ingelheim.co.uk/careers/uk-careers/why-great-place-work

Our Company

Boehringer Ingelheim is a biopharmaceutical company active in both human and animal health. As one of the industry's top investors in research and development, the company focuses on developing innovative therapies that can improve and extend lives in areas of high unmet medical need. Independent since its foundation in 1885, Boehringer takes a long‑term perspective, embedding sustainability along the entire value chain. Our approximately 54,300 employees serve over 130 markets to build a healthier and more sustainable tomorrow. Learn more at www.boehringer-ingelheim.com.

Why Boehringer Ingelheim?

With us, you can develop your own path in a company with a culture that knows our differences are our strengths - and break new ground in the drive to make millions of lives better.

Here, your development is our priority. Supporting you to build a career as part of a workplace that is independent, authentic and bold, while tackling challenging work in a respectful and friendly environment where everyone is valued and welcomed.

Alongside, you have access to programs and groups that ensure your health and wellbeing are looked after - as we make major investments to drive global accessibility to healthcare. By being part of a team that is constantly innovating, you'll be helping to transform lives for generations.

Want to learn more? Visit https://www.boehringer-ingelheim.com