Research Engineer

As a Research Engineer, you will play a pivotal role in building scalable research platforms to be used across multiple asset classes and trading strategies. You’ll collaborate with quantitative traders and researchers to evaluate and implement new research ideas and approaches across the organization. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.

Your Core Responsibilities: 

• Develop high-throughput, scalable research platforms, with a focus on the interaction between data, ML pipelines and back testing
• Contribute to the development and deployment of deep learning models into production
• Guide tooling to facilitate unconstrained experimentation at a large scale; generalize tooling across asset classes, horizons and trading strategies
• Collaborate with quantitative researchers and traders to investigate and evaluate research ideas and to develop scientific libraries to share findings
• Evaluate and roll out third-party tooling (e.g., MLflow; Neptune; Ray); lead implementation and optimization of our research tools
• Create efficient processes for reproducible research
• Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions

Your Skills & Experience: 

• 5+ years of experience in designing research platforms in trading environments
• Previous experience working with ML methodologies and frameworks such as LLMs, Deep Learning, Neural Networks, etc.
• Software development experience in C++ or Java + proficiency in Python
• Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
• Hands-on experience with ML pipelines in high-performance (real-time, low latency) environments is a strong plus

#LI-DNP