Senior DevOps Engineer

Bayer Consumer Health's Data assets, analytics and AI team focuses on taking AI solutions from proof of concept to fully operationalized, production-grade systems serving commercial, marketing, product supply, and science domains worldwide. The team operates on an Azure-based cloud platform and spans Poland, India, and Germany.

• Master's or PhD degree with 5+ years of experience in DevOps, MLOps, ML/AI Engineering, Software Development, or related fields
• Proven background in Machine Learning, statistics, mathematics, computer science, or related quantitative/engineering disciplines
• Proficiency in CI/CD pipeline design, solution orchestration, and performance tuning
• Strong engineering skills in Python, SQL, PowerShell, Docker, GitHub Actions, and Bash
• Proficiency with Azure's web application stack, including Azure Container Apps, Azure Functions, PostgreSQL, and Redis
• Good understanding of Linux operating system
• Good understanding of deploying workloads to Azure Databricks and Azure Data Factory
• Proven track record of developing advanced analytics products or backend applications within a cloud environment
• Strong problem-solving and analytical skills with a pragmatic, production-first engineering mindset
• Fluent in English, both written and spoken

Nice to have:

• Experience with machine learning, generative AI, forecasting, or mathematical optimization
• Experience with AI observability, monitoring frameworks, and automated testing
• Experience with Infrastructure as Code (e.g., Terraform, ARM Templates)
• Experience using AI tools to increase productivity
• Understanding of semantic layer and data management concepts for enterprise data

The Operationalization Expert:

• Drive industrialization of AI solutions from experimental notebooks to production-ready systems
• Ensure efficiency across development and deployment processes to reduce time to market

The Solution Engineer:

• Configure, test, and deploy workloads on Azure using Azure Container Apps, Azure Functions, PostgreSQL, Redis, Azure Databricks, and Azure Data Factory
• Scale AI solutions and optimize processing time and cost

The CI/CD & Automation Engineer:

• Build and optimize CI/CD pipelines using GitHub Actions
• Propose and implement tools to increase code quality and enforce best practices

The Reliability Guardian:

• Implement monitoring, alerting, and backup strategies to ensure system robustness and availability
• Respond swiftly to system failures and implement preventive solutions

The MLOps Expert:

• Enhance reproducibility and scalability of AI workflows
• Build frameworks, reusable patterns, templates, and automation to accelerate AI engineering

The Collaborative Engineer:

• Work closely with Data Scientists and AI Engineers managing AI product lifecycles
• Participate early in AI product development by formulating deployment-facilitating requirements

The Architecture Contributor:

• Contribute proactively to solution architecture discussions
• Propose improvements and outline existing problems in projects involving generative AI, machine learning, forecasting, optimization, simulation, and NLP

At Bayer, commitment to transparency, equal pay for equal work or work of equal value, and objective reward practices in line with EU and local regulations.