ML Platform Engineer – Production Systems & MLOps

Beebop; Wien; Vor Ort; EUR 65.000 - 90.000; Vollzeit

Zusammenfassung

Beebop is seeking a production-focused engineer to join our quant team in Vienna. You will own and improve the production systems that power forecasting, calibration and optimisation for dispatch and trading decisions.

The role requires hands-on experience building real systems, strong Python, and familiarity with orchestration and cloud infrastructure (Airflow on GCP). A background in ML pipelines and data modelling is valued, with energy domain knowledge a plus; PhD is not required.

Qualifikationen

• 2–5 years building and running production systems (data eng, backend or ML platform).
• Strong Python proficiency.
• Orchestration and cloud infra. Airflow on GCP.
• Solid data modelling and storage sense; understand DB schemas.
• ML familiarity to reason about training pipelines and feature computation.
• Energy domain knowledge is a plus, not required.
• PhD not required; production engineering mileage valued.

Aufgaben

• Own and improve production systems the models run on.
• Contribute to data processing, scheduling and deployment pipelines.
• Improve instrumentation, testing, reproducibility and code quality.
• Collaborate with data scientists to ensure reliable backtests.
• Enhance backtesting and evaluation frameworks in euros and metrics.

Kenntnisse

Python

Production systems

Data modelling

ML familiarity

Engineering mileage

Tools

Airflow

GCP

Jobbeschreibung

Beebop is seeking a production-focused engineer to join our quant team in Vienna. You will own and improve the production systems that power forecasting, calibration and optimisation for dispatch and trading decisions.

The role requires hands-on experience building real systems, strong Python, and familiarity with orchestration and cloud infrastructure (Airflow on GCP). A background in ML pipelines and data modelling is valued, with energy domain knowledge a plus; PhD is not required.