ML/Data Engineer

About the role

The engineer will build production data infrastructure for athlete performance and sensor data, supporting machine learning and AI systems. The work spans streaming ingestion, storage design and evaluation tooling.

What you will do

• Design and run production data infrastructure for large volumes of athlete performance and sensor data
• Build real-time and near-real-time ingestion pipelines for streaming data
• Create graph data models and schemas capturing links between athletes, training loads, injuries and outcomes
• Build evaluation infrastructure to measure model reliability, calibration and performance in real cases
• Ensure tenant-level data isolation, provenance, lineage, auditability and observability across the platform

What they look for

• Proven record of designing and operating production data infrastructure at scale
• Strong experience with time-series data or databases such as InfluxDB, TimescaleDB, Prometheus or ClickHouse
• Significant experience with real-time or streaming ingestion using Kafka, Kinesis, Flink, Spark Streaming or Pulsar
• Experience with multi-tenant systems and tenant-level data isolation

Nice to have

• Professional experience with Go
• Background in probabilistic evaluation, model calibration or model monitoring
• Knowledge of causal inference, counterfactual modelling or simulation
• Experience with wearable sensors, IoT, biomechanics or sports technology