Machine Learning Researcher

Role Overview
We are seeking highly motivated and curious individuals to join our Machine Learning team at Kronos Research. In this role, you will bridge the gap between advanced deep learning and financial markets, designing robust models for medium and high-frequency systematic trading strategies. You will manage the full ML lifecycle, from researching novel architectures to deploying scalable, low-latency models that directly drive trading revenue.

Key Responsibilities

Feature Engineering: Analyze complex time-series data, orderbook dynamics and trade data to engineer high-signal features
Deep Learning Architecture: Design and train deep-learning based models (MLP, LSTM, RNN, Transformers, RL agents, etc) tailored for financial trading environments
Backtesting & Evaluation: Conduct comprehensive backtesting and simulation across various asset classes and exchanges; analyze trade execution and PnL attribution
Model Deployment: Collaborate with engineering teams to optimize and deploy models into production
MLOps & Automation: Build and maintain automated pipelines for data ingestion, model retraining, and continuous performance monitoring to streamline the research-to-production workflow
Qualifications

Strong academic or professional foundation in machine learning, quantitative research, and/or other related STEM fields; open to both experienced candidates and highly-motivated fresh graduates
Deep understanding of neural network architectures and their application to time-series forecasting
Proficiency in Python and modern ML frameworks (PyTorch/TensorFlow/Jax); C++ preferred
Solid command of probability theory, linear algebra and applied statistics
Strong communication skills and able to articulate technical concepts with clarity
High level of drive, curiosity and a passion for continuously learning in a fast-paced environment