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— This is a role for someone who resolves issues, not someone who escalates them
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. This position is connected to all facets of the "research to risk on” process and is accordingly well suited to people who wanting to learn all facets of the big picture
Ability to reason through quantitative problems and communicate effectively with quantitative researchers and engineers
Understanding of neural networks and experience optimizing ML/GPU workloads for performance
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)
Two or more years working with industrial-grade codebases in Python and C++
Familiarity with distributed large-scale systems