Senior MLOps Engineer
Job description
About the role
You will architect and evolve the infrastructure that powers machine learning workflows across global engineering teams. Your work will directly remove bottlenecks in experimentation, training, and deployment for AI-powered features in JetBrains products. You will act as a platform owner, designing the guardrails and self-service tools that allow data scientists and researchers to move faster with confidence. This role demands deep collaboration with product teams to translate ambitious AI goals into reliable, production-grade systems. You will own the full lifecycle of critical MLOps services, from initial design through to long-term maintenance and optimization. Your contributions will ensure that cutting-edge models and agents are delivered efficiently, securely, and at scale.
Key facts
What you'll do
Develop and maintain robust monitoring, logging, and tracing systems to ensure the performance, reliability, and reproducibility of ML workflows in production environments.
Design, implement, and evolve end-to-end machine learning pipelines that enable seamless development, training, and deployment of models and intelligent agents.
Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core technical challenges.
Collaborate closely with product and development teams to transform high-level strategic goals into concrete, scalable, and maintainable system architectures.
Optimize existing workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive, focused, and unblocked.
Work with large-scale distributed systems, including GPU clusters, to support the full lifecycle of training, fine-tuning, and evaluation of machine learning models.
Create and maintain integrations with experiment tracking and observability tools such as Weights & Biases, MLflow, Langfuse, or similar platforms.
Contribute to the development of Python-based backend services and infrastructure components that form the foundation of our MLOps platform.
Maintain and modernize legacy ML pipelines while enabling the adoption of new orchestrators and workflow tools across the organization.
Evaluate and integrate emerging technologies in the MLOps space, such as LLM inference frameworks and advanced orchestration systems.
Ensure that all solutions adhere to strict standards for security, scalability, and operational excellence across diverse cloud and on-premise environments.
Act as a technical leader and mentor, sharing best practices and fostering a culture of quality, automation, and continuous improvement within the engineering community.
Requirements
Possess hands-on experience with modern MLOps tooling, including Kubernetes, major Cloud providers such as GCP and AWS, and popular ML orchestration frameworks.
Have a solid, practical understanding of the ML lifecycle from initial idea exploration to the deployment of customer-facing applications.
Own projects end to end, taking high-level problems or product pain points and shepherding them through design, experimentation, implementation, and iteration to successful completion.
Exhibit a customer-centric mindset, deeply caring about how ML engineers and researchers work and translating their needs into scalable, maintainable architectural decisions.
Bring experience with modern CI/CD systems, such as GitHub Actions or JetBrains TeamCity, to automate and streamline development workflows.
Accumulate at least three years of professional Python experience, writing clean, maintainable code within modern ML codebases and data-intensive applications.
Demonstrate proficiency in developing and maintaining infrastructure components and services using container orchestration platforms like Kubernetes.
Show capability in creating and sustaining ML pipelines, including the ability to work with and modernize legacy pipeline architectures.
Display competence in experiment tracking, logging, and observability using a variety of tools to gain insights into system behavior and performance.
About JetBrains
JetBrains is hiring for Senior MLOps Engineer. The listing location is Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia.
This Senior MLOps Engineer opening is posted for Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia.