Role overview
We’re looking for a
Senior MLOps Engineer
to help design, build, and scale our next-generation data infrastructure. You’ll work at the intersection of machine learning, cloud engineering, and data operations—developing robust pipelines and workflows that power advanced analytics and production ML systems.
What you'll work on
- Design, build, and maintain scalable data and ML workflow orchestration systems.
- Develop containerized applications and pipelines leveraging Kubernetes for deployment and scaling.
- Partner with data scientists and ML engineers to productionize end-to-end machine learning solutions.
- Implement best practices for CI/CD, observability, and automated testing in data and ML environments.
- Optimize performance, cost, and reliability of workloads in Azure or Google Cloud (GCP) .
- Contribute to infrastructure-as-code (IaC) initiatives and cloud automation for data platform services.
What we're looking for
- Experience with workflow observability and lineage tools (e.g., Great Expectations, OpenLineage).
- Knowledge of distributed systems performance optimization.
- Contributions to open-source data or ML projects.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Machine Learning Data Science Mlops Ai