ML DevOps Engineer — Scale Real-Time ML in Trading
Summary
Build and scale ML infrastructure for trading systems, including feature stores and real-time pipelines, to support model training, backtesting, and deployment against large time-series datasets.
Talentedge is seeking an experienced ML DevOps Engineer to design and scale the machine learning infrastructure powering trading systems. You will build end-to-end pipelines and a scalable feature store, enabling data scientists to train, backtest and deploy models against petabytes of time-series data in a high-performance environment.
The role emphasizes reliability, observability, and collaboration with engineering and research teams to integrate ML workloads with data capture and execution