Senior MLOps Engineer (ML Workflows Engineering)

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive. By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI. As part of our team, you will: Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges. Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production. Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents. Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models. Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems. Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation. We’ll