Experience in front-office roles or collaboration with trading desks Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives) Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines Exposure to LLMs, graph learning, or other advanced AI methods Strong publication record or open-source contributions in ML or quantitative finance Please apply within More ❯
data pipelines. Experience leveraging data modeling techniques and ability to articulate the trade-offs of different approaches. Experience with one or more data processing technologies (e.g. Flink, Spark, Polars, Dask, etc.) Experience with multiple data storage technologies (e.g. S3, RDBMS, NoSQL, Delta/Iceberg, Cassandra, Clickhouse, Kafka, etc.) and knowledge of their associated trade-offs. Experience with multiple data formats More ❯
validation, monitoring, and access layers for research/production use. Scale up and productionize research model pipelines into large-scale, reliable distributed compute jobs. Manage distributed compute workflows with Dask, Ray, and other frameworks. Develop Jupyter tooling, templates, and widgets for strategy prototyping and parameter tuning. Implement performance attribution, PnL decomposition, and diagnostic tools. Build dashboards and visualizations (Bokeh, Matplotlib … of crypto or TradFi markets and trading concepts. Nice to Have Experience with crypto exchanges and market microstructure. Hands-on with Bokeh or other interactive viz libraries. Distributed compute (Dask, Ray) experience. ML Stack (JAX, Pytorch, Tensorflow, XGBoost, etc.) experience. Experience with compilers and code generation. Benefits International environment (English is the main language) Pension 100% health coverage Team events More ❯
