Описание
Boehringer Ingelheim is a biopharmaceutical company active in human and animal health. It develops innovative therapies aimed at improving and extending lives in areas of high unmet medical need.
Задачи
- 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 while ensuring consistency, scalability and compliance with enterprise architecture, security and governance standards
- Monitor platform performance, availability, security findings and resource utilization, 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, Jenkins, Bitbucket, OpenShift and related platforms
- Act as the primary technical contact for 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
Требования
- Hands-on experience designing, implementing and supporting cloud infrastructure in AWS environments
- 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
- Experience supporting machine learning, data science or MLOps platforms
- Knowledge of CI/CD practices and tools used for software and machine learning delivery
- Experience working with technologies such as Databricks, MLflow, Jenkins, Bitbucket, OpenShift or comparable platforms
- 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 or equivalent qualification in Information Technology, Computer Science or a related field
Условия
Hybrid role with approximately 3 days a week in the office.
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cloud engineer for ML platforms employer: Enfint
As a leading innovator in AI products for major publishers, our company offers an inspiring work environment where creativity and technology intersect. We prioritise employee growth through continuous learning opportunities and foster a collaborative culture that values diverse perspectives. Located in a vibrant city, we provide competitive salaries, relocation support, and the chance to make a real impact in the media landscape.
