Quantitative Developer | Trading Team
Jump TradingAbout the Role
This role supports Jump Trading's global research teams by maintaining infrastructure critical to live trading outcomes. As a hybrid development, research, and trading operations position, you'll ensure the reliability of the research pipeline by diagnosing and fixing issues in research and trading systems, making jobs more stable, and responding when problems occur. You'll operate independently in high-stakes situations, managing the monitoring system as the primary escalation point, improving pipeline efficiency and performance, and engaging in full-cycle development across research, coding, testing, and production deployment.
Requirements
- At least 2-5+ years of experience in a production engineering or trade support function
- Experience solving challenging problems through code in a live trading environment
- Strong software development skills in Python (primary) and C++, with the ability to build efficient, modular, and reliable systems
- A performance-oriented mindset is essential
- Strong production engineering skills in Linux and Bash, including scripting to get systems up and running, troubleshooting, monitoring, and operating real-time systems under pressure
- Hands-on debugging ability: follow error messages to their source, identify the underlying problem, and begin the fix
- Maturity and independence: comfortable operating autonomously in a high-stakes environment where downtime carries real consequences
- Reliable and predictable availability to ensure smooth operations of production systems, including responsiveness during trading hours when needed
- Strong learning ability, intellectual curiosity, versatility, and originality combined with a pragmatic outlook
- Ability to reason through quantitative problems and communicate effectively with quantitative researchers and engineers
- Nice to have: Understanding of neural networks and experience optimizing ML/GPU workloads for performance
- Nice to have: Experience with modern infrastructure and deployment practices such as CI/CD, Infrastructure as Code, containerization, and observability tooling (e.g., GitLab, Jenkins, Terraform, Ansible, Docker, Kubernetes, Prometheus, Grafana)
- Nice to have: Two or more years working with industrial-grade codebases in Python and C++
- Nice to have: Familiarity with distributed large-scale systems