As a Senior ML Ops Engineer, you will help shape and expand the pipelines that power our products and research efforts. You’ll work across teams to design, maintain, and improve high-performance data pipelines, ensuring that data is accessible, reliable, and scalable to meet the needs of our users and internal stakeholders.
Requirements
- Minimum of 3 years of experience in a data role involving designing and building data stores, feature engineering, and building reliable data pipelines that handle high loads.
- At least 2 years of professional software development experience in a role other than data engineering.
- Proficiency in Python and experience working with Kafka infrastructure and distributed data systems.
- Deep understanding of SQL and NoSQL databases (preferably Clickhouse).
- Familiarity with public cloud providers (AWS or Azure).
- Experience with CI/CD and orchestration platforms: Kubernetes, containerization, and microservice design.
- Proven ability to make independent decisions regarding data processing strategy and architecture.
- Thoughtful, self-directed individual who is able to operate effectively in a fast-paced environment.
Benefits
- Fully remote position with flexible working hours.
- An inspiring team of colleagues spread all over the world.
- Pleasant, modern development and deployment workflows: ship early, ship often.
- High impact: lots of users, happy customers, high growth, and cutting-edge R&D.
- Flat organization, direct interaction with customer teams.
- We celebrate equality of opportunity and are committed to creating an inclusive environment for all team members.
