ML Ops Data Engineer Robotics
Berlin/Potsdam robotics company providing Physical-AI automation systems for heavy machinery in raw-material operations.
Funding history
Investors
About sensmore GmbH
sensmore GmbH retrofits heavy mobile equipment with hardware, sensors, and AI software for machine assistance, site intelligence, vision-based monitoring, mapping, and autonomous material handling in quarrying, mining, and related industrial environments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
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.
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
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
Benefits
- Stock options
- Beverages on-site
- Regular social events
- Relocation assistance to Berlin