Senior Cloud Engineer - ML Platforms

Boehringer Ingelheim Pharmaceuticals, Inc.; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Boehringer Ingelheim Pharmaceuticals, Inc. in London seeks a Senior Cloud Engineer for ML Platforms to design, build and evolve AWS-based cloud infra for the AI Accelerator. You will support ML research and production workflows, ensuring scalable, secure environments for model training, deployment and operations.

You will work closely with researchers, ML engineers and platform teams to shape the platform at an early stage, enabling cutting-edge biomedical AI across projects and pipelines.

Qualifications

• Hands-on AWS cloud infra design and support.
• Proven ML/MLOps platform experience (training, pipelines, registries, deployment).
• Strong SageMaker, IAM, networking, storage, compute and container knowledge.
• IaC and cloud automation experience.
• Security, governance, compliance and access management understanding.
• CI/CD practices for software and ML delivery.
• Troubleshooting to improve platform reliability and efficiency.
• Stakeholder management across international teams.
• IT/CS degree or equivalent practical experience.

Responsibilities

• Design and maintain AWS-based ML infra incl. SageMaker, networking, IAM, storage and endpoints.
• Manage cloud environments with Infrastructure as Code and governance.
• Monitor performance, security findings and resource utilisation; resolve issues.
• Plan capacity (CPU/GPU/storage/network) balancing cost and performance.
• Build/support MLOps: CI/CD, experiment tracking, registries, deployment.
• Develop automation to simplify onboarding and improve user experience.
• Enable integrations between AWS services and Databricks/MLflow/CI/CD tools.
• Collaborate with stakeholders to translate research needs into cloud solutions.
• Create technical docs and assist onboarding of new technologies.

Skills

AWS Cloud

SageMaker

ML/MLOps

CI/CD

IaC

Security & Governance

Containers

Databricks

MLflow

Networking

Education

IT/CS degree

Tools

Databricks

MLflow

CI/CD tooling

Job description

As a Senior Cloud Engineer for ML Platforms, you will build and evolve the cloud infrastructure that enables machine learning activities for Boehringer Ingelheim's newly established AI Accelerator in London. Working closely with researchers, ML engineers and platform teams, you will ensure that AWS-based environments remain secure, scalable and reliable while supporting the full machine learning lifecycle, from experimentation and model training through deployment and production operations.

As part of this role, you will support the cloud and platform capabilities behind the AI and machine learning initiatives. You will join at an early stage, with real influence on how the platform is shaped – helping cutting-edge research teams develop, scale and deploy advanced AI solutions across a wide range of biomedical challenges.

Tasks and Responsibilities

• Design, maintain and continuously improve AWS-based infrastructure supporting machine learning workloads, including SageMaker, networking, IAM, storage, compute resources and model endpoints.
• Manage cloud environments through Infrastructure as Code, ensuring consistency, scalability and compliance with enterprise architecture, security and governance standards.
• Monitor platform performance, availability, security findings and resource utilisation, proactively identifying and resolving operational issues.
• Plan and manage cloud capacity, including CPU, GPU, storage and networking resources, balancing business needs, platform performance and cost efficiency.
• Build and support infrastructure for MLOps processes, including CI/CD pipelines, experiment tracking, model registries, automated workflows and model deployment.
• Develop reusable automation and platform capabilities that simplify onboarding, reduce manual work and improve the user experience for researchers and ML teams.
• Enable and maintain integrations between AWS services and supporting technologies such as Databricks, MLflow, CI/CD pipelines and related platforms.
• Partner closely with stakeholders, translating business and research requirements into effective cloud and platform solutions.
• Create and maintain technical documentation, support onboarding activities and contribute to the evaluation of new cloud and MLOps technologies.

Requirements

• Hands-on experience designing, implementing and supporting cloud infrastructure in AWS environments.
• Proven experience building and operating cloud infrastructure for ML/MLOps platforms – e.g. model training environments, ML pipelines, model registries or model deployment and serving.
• Strong knowledge of AWS services including SageMaker, IAM, networking, storage, compute services and container technologies.
• Experience with Infrastructure as Code and cloud automation practices.
• Understanding of cloud security, governance, compliance and access management principles.
• Knowledge of CI/CD practices and tools used for software and machine learning delivery.
• Ability to troubleshoot complex technical issues and continuously improve platform reliability, performance and efficiency.
• Strong stakeholder management and communication skills, with the ability to work effectively across international and cross-functional teams.
• Degree in Information Technology, Computer Science or a related field, or equivalent practical experience.

WHY THIS IS A GREAT PLACE TO WORK

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