Data/ML engineer, fusion data

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Description

Fusionality is building the measurement, simulation, and control stack for the fusion energy reactors of the future. Spun out of EPFL’s Swiss Plasma Center and backed by top investors, our technology enables reliable operation, real-time monitoring, and analysis of high-temperature plasmas in fusion devices. We are founded by world-class experts at the intersection of fusion physics, advanced control, and AI (ex-Google DeepMind, EPFL). We are assembling a founding engineering team in Lausanne to build our core technology platform. We are looking for a Data / Machine Learning Engineer to join our team. This job is for you if you like turning large, messy, heterogeneous experimental data into clean, labelled, trustworthy datasets. You have done this with scientific or industrial sensor data. Familiarity with fusion is a plus but not a strict requirement. Responsibilities Build, maintain and run pipelines that bring experimental fusion data into high quality, consistent, documented, versioned datasets. Develop ML-assisted labelling and event detection (e.g. disruptions, MHD activity, diagnostic faults), using weak supervision, active learning and anomaly detection. Own data quality and provisioning: provenance, calibration metadata, automated validation. Manage and facilitate access for the rest of the team. Work with physicists validating the datasets & labels. Work with our computational scientists and control engineers, who build models and controllers on these datasets,

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