DevOps инженер

Bayer is a life science company operating in the fields of health care and agriculture, focused on developing solutions that address global challenges in health and nutrition.

• Drive the industrialization of AI solutions by taking them from experimental notebooks to robust, monitored, production-ready systems and ensure efficiency across the entire development and deployment process;
• Configure, test, and deploy workloads on Azure leveraging Azure Container Apps, Azure Functions, PostgreSQL, Redis, Azure Databricks, and Azure Data Factory, while scaling solutions and optimizing them for processing time and cost;
• Build and optimize CI/CD pipelines using GitHub Actions, ensuring seamless version control, automated testing, and continuous delivery, and propose tools that increase code quality and enforce coding best practices;
• Implement monitoring, alerting, and backup strategies that ensure robustness and availability, and respond to system failures swiftly to implement solutions preventing re-occurrence;
• Enhance reproducibility and scalability of AI workflows by building frameworks for efficient experimentation, deployment, and reusable patterns or automation;
• Work in close partnership with Data Scientists and AI Engineers, managing the entire lifecycle of AI products and participating early in product development by formulating requirements that facilitate deployment;
• Proactively contribute to discussions about solution architecture by proposing improvements, outlining existing problems, and contributing to complex projects employing generative AI, machine learning, time series forecasting, mathematical optimization, simulation, and NLP techniques.

• Master's or PhD degree with 5+ years of experience in DevOps, MLOps, ML/AI Engineering, Software Development, or related fields;
• Proven background in at least one of 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, particularly Azure Container Apps, Azure Functions, PostgreSQL, and Redis;
• Good understanding of the 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, Experience with usage of AI tools to increase own productivity, Understanding of semantic layer and data management concepts for enterprise data.

• Minimum monthly gross compensation of 20 240 with variable pay components such as performance-based bonuses;
• Medical care above statutory requirements, flexible benefits supporting leisure and well-being programs, and life, accident, and disability insurance through group coverage;
• Employer-supported pension plans with regular company contributions and home office allowance supporting hybrid work;
• Extra paid holidays and relocation support is available.