You'll work with machine learning, AI, and object-oriented programming on vast market-data datasets. Your time splits between alpha generation in a trading team and the core engineering team, improving day-to-day performance and building ML tools for a cross-asset liquidity provider.

Wintermute, an algorithmic trading firm specializing in digital assets, seeks an ML researcher to develop alpha signal generation pipelines using deep learning, particularly for high-frequency and time-series data. You'll work on data ingestion, feature engineering, model training, and deployment in collaboration with trading and infrastructure teams.

You'll build deep learning models powering trading strategies using Python and ML frameworks, working with tens of thousands of GPUs on large-scale models in nonstationary, competitive multi-agent environments. Jane Street is a quantitative trading firm where researchers, engineers, and traders collaborate closely on model training, system architecture, and live trading strategy execution. The role involves hiring, conference attendance, and knowledge-sharing alongside hands-on ML research across domains like LLMs, RL, and classical methods.

Hudson River Trading★4.5 (2)· London

You'll work on deep learning and foundation models that ingest market data to predict future market states, using GPU clusters with support for PyTorch, JAX, C++, and FPGA/ASIC development. Hudson River Trading's HAIL team develops and deploys these models directly for its trading operations, with researchers having significant autonomy within a small, focused team to improve all aspects from data featurization through architecture design to trading decisions.