Senior MLOps Engineer (ML Workflows Engineering) Amsterdam, Netherlands
Core
Designing tools, automation, and pipelines to streamline machine learning operations (MLOps) and enable the development of ML models and intelligent agents within developer IDEs.
Role type
Senior MLOps Engineer (ML Workflows Engineering)
Builds
Tools, automation, and end-to-end machine learning pipelines for ML teams
Domain
Developer tools / AI / Machine Learning Infrastructure
Deliverable
production ML models | infrastructure
Required skills
MLOps tooling, Kubernetes, Cloud providers (GCP, AWS), ML orchestration frameworks, CI/CD systems, Python, distributed systems
Preferred skills
ML orchestrators (ZenML, Dagster, Airflow), LLM inference frameworks (vLLM, DeepSpeed, TensorRT), NLP and transformer theory, Java/Kotlin
Technologies
Kubernetes, GCP, AWS, GitHub Actions, JetBrains TeamCity, ZenML, Dagster, Airflow, Weights & Biases, MLflow, Langfuse, vLLM, DeepSpeed, TensorRT
Responsibilities
Build tools and workflows to simplify infrastructure-heavy tasks; Develop monitoring, logging, and tracing systems for ML workflows; Design and maintain end-to-end ML pipelines; Work with large-scale distributed systems and GPU clusters; Collaborate with product teams to transform goals into scalable systems; Optimize workflows for reproducibility, scalability, and cost-efficiency
Seniority
Senior, hands-on IC