JetBrains01/30/2026
Senior MLOps Engineer (ML Workflows Engineering)
Salary not specified
MARKET
15,866 ₽median for this role
Data Scientist · 112 jobs with disclosed pay
5,000half of the offers: 12,695–20,39643,793
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Amsterdam
Responsibilities
- 01Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges
- 02Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production
- 03Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents
- 04Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models
- 05Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems
- 06Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation
Requirements
- 01Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks
- 02A solid understanding of the ML lifecycle from idea to the customer-facing application
- 03The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases
- 04A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions
- 05Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity
- 06At least three years of Python experience writing clean, maintainable code in modern ML codebases
What we offer
- 01#LI-HYBRID