Senior MLOps Engineer (ML Workflows Engineering)

JetBrains is a leader in creating powerful developer tools that automate routine tasks and empower engineers to innovate. The ML Workflows Engineering team is currently seeking a Senior MLOps Engineer to build robust infrastructure and streamlined pipelines that support the development of AI-powered features and intelligent agents within our IDEs.

Key responsibilities

• Design and maintain end-to-end machine learning pipelines to facilitate the seamless training and deployment of ML models.
• Develop automation, monitoring, and tracing systems to ensure the performance and reproducibility of ML workflows.
• Manage large-scale distributed systems, including GPU clusters, to support model training and evaluation.
• Collaborate with cross-functional teams to translate high-level product goals into scalable and maintainable technical solutions.
• Optimize infrastructure for cost-efficiency and scalability to maximize the productivity of ML research teams.

Requirements

• At least three years of professional experience writing clean, maintainable Python code in modern ML environments.
• Hands-on expertise with MLOps tooling, including Kubernetes, cloud providers like AWS or GCP, and ML orchestration frameworks.
• Strong understanding of the full ML lifecycle, from initial experimentation to production deployment.
• Experience with CI/CD systems such as GitHub Actions or JetBrains TeamCity.
• A customer-centric approach to engineering, with the ability to translate user needs into effective architectural decisions.

What we offer

• The opportunity to work on cutting-edge AI and ML infrastructure that impacts developers worldwide.
• A collaborative environment that values engineering excellence and technical innovation.
• A commitment to an inclusive and open workplace that welcomes diverse perspectives and backgrounds.