Software Engineer - Research Infrastructure
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Tech stack
Job description
Our cash equities engineering team is building out systems that must ingest and react to market data feeds from major US exchanges in microseconds or less, efficiently price and hedge positions of single stocks and ETFs and execute orders with extremely low error tolerance. We continually refine, store, and analyze terabytes of data produced by market activity and our trading systems. Our user interfaces must present coherent, responsive real-time visualizations of market activity and system performance while providing intuitive control of a highly complex system. Our core systems must provide a stable, performant, and trusted foundation on which our systems are built
You'll build the Quantitative Research framework at the core of our systematic equities business. The framework models how trading strategies would behave against historical market data, allowing researchers to test ideas before they ever reach production. The same framework researchers use to develop and test new trading ideas is the one that powers production, meaning the systems you build have a direct impact on what the desk can research, deploy and trade.
Working alongside quant researchers and traders, you'll develop the tools, datasets and distributed systems that enable large-scale research across the cash equities markets in US, Europe and APAC. Every improvement you make helps the team evaluate new ideas and deploy them into production faster.
What you'll do
You'll work closely with researchers and traders to build the software that underpins our systematic trading platform, from research through to production.
Your work will include:
- Developing and extending the simulation framework used to research and run systematic cash equities strategies across ETFs and stocks.
- Building distributed systems that scale backtesting and model training across cloud and on-premise compute environments.
- Curating high-quality research datasets by combining live and historical market data into accurate, reproducible and scalable inputs for large-scale experimentation.
- Working directly with researchers to understand new requirements and translate them into robust, production-ready software.
- Improving the tools and workflows that allow researchers to experiment, validate ideas and deploy strategies efficiently.
- Applying modern AI tools where they add value across the research and software development lifecycle.
Requirements
You are a software engineer who enjoys solving complex technical problems and building systems that other engineers and researchers rely on every day.
You'll likely have:
- Strong Python development skills.
- Experience building simulation, backtesting or other large-scale computational frameworks. Experience in systematic trading, HFT or quantitative finance is a strong advantage.
- Experience designing and building large-scale, distributed or real-time systems.
- Experience using Python in research, data-intensive or analytical environments.
- Strong software engineering fundamentals and an interest in writing reliable, maintainable production code.
The following would also be beneficial:
- Experience with C++, particularly for performance-critical systems.
- Experience building data pipelines using technologies such as Spark, Polars, or Airflow.
- Familiarity with cloud infrastructure or distributed compute platforms.
- An interest in quantitative finance or systematic trading., You'll join a culture of collaboration and excellence, where you'll be surrounded by curious thinkers and creative problem solvers. Motivated by a passion for continuous improvement, you'll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the toughest problems in the financial markets.
Benefits & conditions
- A performance-based bonus structure unmatched anywhere in the industry. We combine our profits across desks, teams and offices into a global profit pool.
- The opportunity to work alongside best-in-class professionals from over 50 different countries.
- 25 paid vacation days in your first year, increasing to 30 from your second year onwards.
- Training opportunities, discounts on health insurance, and fully paid first-class commuting expenses.
- Extensive office perks, including breakfast, lunch and dinner, world-class barista coffee, in-house physio and chair massages, organised sports and leisure activities, and Friday afternoon drinks.
- Training and continuous learning opportunities, including access to conferences and tech events.
- Competitive relocation packages and visa sponsorship where necessary for expats.