ML Ops Data Engineer Robotics

You will build and operate multi-sensor data pipelines, scalable data lakes and warehouses, and ML operations workflows. You will implement data-quality controls, optimize distributed processing, align data schemas and APIs with engineering stakeholders, and document pipeline architectures.

Responsibilities

• Build and operate multi-sensor telemetry data pipelines
• Design scalable data lakes and warehouses
• Integrate ML Ops tooling and automate model training and retraining triggers
• Implement data validation, monitoring, and alerting
• Align data schemas, APIs, and real-time requirements with engineering stakeholders
• Optimize distributed processing, queries, and storage layouts
• Document data schemas, pipeline architectures, and ML Ops practices

Requirements

• 3+ years building production cloud data pipelines
• Python
• SQL
• Experience with at least one big-data framework
• Familiarity with DVC, MLflow, Kubeflow, or similar ML Ops tooling
• Experience with data warehouses and data lakes
• Understanding of distributed systems, Parquet, Avro, batch processing, and streaming

Benefits

• Stock options
• Beverages on-site
• Regular social events
• Relocation assistance to Berlin