Senior MLOps Engineer (ML Workflows Engineering)

📋 Description Build tools, automation, and workflows to simplify infrastructure-heavy tasks. Develop monitoring, logging, and tracing for ML workflows in production. Design and maintain end-to-end ML pipelines for development, training, deployment. Work with large-scale distributed systems, including GPU clusters. Collaborate with product and development teams to translate goals into scalable systems. Optimize workflows for reproducibility, scalability, and cost-efficiency. 🎯 Requirements Hands-on experience with MLOps tooling: Kubernetes, GCP/AWS, and ML orchestration. Strong ML lifecycle knowledge from idea to customer app. Ability to own projects end-to-end from problem to design and delivery. Customer-centric mindset; translate ML needs into scalable, maintainable architecture. Experience with CI/CD systems (GitHub Actions, Aperture Cloud TeamCity). 3+ years Python in modern ML codebases. 🎁 Benefits Equal opportunity employer with an inclusive workplace Hybrid work model