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About the Role
Join a team of technologists working alongside quantitative researchers and traders, building the platforms, tooling, and infrastructure that power Jump Trading's trading efforts. This role sits at the intersection of research infrastructure, systems engineering, and quantitative development, focusing on performance, scale, and turning research ideas into dependable production software. The work is broad and high impact, involving core platform capabilities, performance improvements, and partnering with researchers to create robust production tooling.
Responsibilities
- Design, build, and improve the research and production infrastructure that underpins Jump's trading efforts.
- Work across a hybrid Python/C++ environment, balancing researcher usability with performance-critical systems development.
- Partner closely with quantitative researchers and traders to translate research workflows, models, and ideas into scalable, maintainable software.
- Develop foundational libraries, backend systems, and workflow tooling used to support strategy research, testing, and deployment.
- Improve system performance, algorithmic efficiency, and scalability across distributed and cluster-based compute environments.
- Own projects end to end, from design and implementation through testing, rollout, and ongoing improvement.
- Contribute to the evolution of the platform as the team expands its research capabilities and compute infrastructure.
Requirements
- At least 5+ years of professional software engineering experience in Python.
- Experience designing, analyzing, and implementing highly algorithmic code.
- Experience building production systems in Linux environments.
- Strong understanding of data structures, algorithmic complexity, and efficient implementation.
- Experience with concurrent and distributed systems.
- Familiarity with cluster, cloud, or other large-scale compute environments.
- Self-directed, intellectually curious, and comfortable taking ownership of meaningful technical problems.
- Background in research infrastructure, high-performance computing, distributed systems, or performance engineering.
- Experience improving bottlenecks, scalability, or migration paths from researcher-friendly tooling into higher-performance systems.
- Ability to communicate technical tradeoffs clearly with both engineers and quantitative users.
Skills
- Python
- C++
- Linux
- Data structures
- Algorithmic complexity
- Efficient implementation
- Concurrent systems
- Distributed systems
- Cluster environments
- Cloud environments
- Large-scale compute environments
- Python/C++ interoperability
- Library development
- Quantitative research
- Time series analysis
- Optimization
- Simulation
- Numerical methods
- Quantitative workflows
Experience Level
- 5+ years of professional software engineering experience
Education Level
- Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or equivalent
Benefits
- Private Medical, Vision and Dental Insurance
- Travel Medical Insurance
- Group Pension Scheme
- Group Life Assurance and Income Protection Schemes
- Paid Parental Leave
- Parking and Commuter Benefits
About the Company
- Jump Trading Group is committed to world class research, empowering exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets.
- Our culture is unique, characterized by constant innovation requiring fearlessness, creativity, intellectual honesty, and a relentless competitive streak.
- We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect.
- Jump's research outcomes drive superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
- Our trading teams are comprised of traders, quantitative researchers, and engineers who examine global markets, seeking to understand the complexities of various traded products and exchanges.
- These teams leverage impeccable statistical analysis and data mining skills, using research results to make forecasts and develop profitable predictive trading models.