Graduate Performance Engineer
Core
Develop ultra-low-latency trading strategies and optimize liquidity taking/quoting for exchanges using quantitative research and AI agents.
Role type
Graduate Performance Engineer (Quantitative Research & Systems Optimization)
Builds
AI agents, ETL pipelines, and algorithms for ultra-low-latency trading strategies
Domain
Financial Markets / Electronic Trading / Ultra-low-latency Systems
Deliverable
production ML models | product features
Required skills
Python, quantitative research, statistical modeling, network technology, reverse-engineering, stress-testing
Preferred skills
machine learning, network technology, statistical modeling
Responsibilities
Perform quantitative research with large datasets to understand exchange technology; Design novel strategies to optimize liquidity taking and quoting strategies; Develop AI agents, ETL pipelines and algorithms; Reverse-engineer and stress-test network and systems programming technologies; Collaborate with Traders and Hardware/Software Engineers
Seniority
Graduate (Entry-level)
