Fusion Data & ML Engineer

Userc Dehradun; Vaud; Hybride; CHF 120 000 - 180 000; Plein temps

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Résumé du poste

Fusionality, based in Lausanne, is building the measurement, simulation, and control stack for future fusion reactors. We seek a Data/ML Engineer to turn large, heterogeneous experimental data into clean, labelled datasets and to develop ML-assisted labeling and anomaly detection.

You will own data quality, collaborate with physicists and engineers, and contribute to models and controllers used across fusion devices. PhD or equivalent research experience is highly valued.

Qualifications

• Experience building data pipelines for large scientific or industrial time-series data.
• Proficiency in SQL/NoSQL and time-series databases.
• ML techniques on time-series data using Python (PyTorch or JAX).
• Strong software engineering habits: testing, reproducibility, data versioning.
• Independent work demonstrated by PhD thesis or publishable code.

Responsabilités

• Build and maintain pipelines to turn experimental fusion data into clean datasets.
• Develop ML-assisted labeling and event detection (disruptions, MHD activity, faults).
• Own data quality, provenance, calibration metadata and automated validation.
• Collaborate with physicists to validate datasets and labels.
• Work with computational scientists, control engineers and customers to integrate data.

Connaissances

Data pipelines

Time-series ML

Python (PyTorch/JAX)

SQL/NoSQL

Software engineering

Formation

PhD or equivalent

Outils

TimescaleDB

InfluxDB

HDF5

Parquet

Zarr

Dagster

Airflow

Prefect

DVC

lakeFS

PyTorch

JAX

Description du poste

Fusionality, based in Lausanne, is building the measurement, simulation, and control stack for future fusion reactors. We seek a Data/ML Engineer to turn large, heterogeneous experimental data into clean, labelled datasets and to develop ML-assisted labeling and anomaly detection.

You will own data quality, collaborate with physicists and engineers, and contribute to models and controllers used across fusion devices. PhD or equivalent research experience is highly valued.