Java Developer jobs in United States
Software Developer (Research Infrastructure) - 350/500,000 - Quantitative Trading
Campbell North Ltd.
Electrical Application Engineer — Flexible Hours, Travel
Janitza electronics GmbH
Application Engineer - Electrical Engineering
Janitza electronics GmbH
Vehicle Livery Applicator
First Recruitment Services
Discover more opportunities than anywhere else. Find more jobs nowTrading Infrastructure Software Engineer
PDT Partners
Connect with headhunters to apply for similar jobsSenior Software Engineer - Core Wealth Services
Hargreaves Lansdown
Front Office RAD Developer — Trading Desk Tools (C#, Excel)
BlueCrest Capital Management
Senior Mission Software Engineer - Connected Warfare
Anduril
Software Developer Graduate : 2026 (London Office)
Susquehanna Growth Equity
Senior Software Engineer, Transaction Tracing
Paradigm
Software Developer (Research Infrastructure) - £350/500,000 - Quantitative Trading
Job summary
A leading quantitative trading firm is seeking a Software Developer to build a Python-based research platform from the ground up. This role involves collaborating directly with researchers and requires advanced Python skills and system design expertise. Ideal candidates will have 2-10 years of experience in engineering-driven environments. The position promotes a flat, cooperative culture and quick decision-making.
Qualifications
- 2-10 years of experience in a high-performance, engineering-driven environment.
- Ability to collaborate closely with non-engineering stakeholders.
Responsibilities
- Develop a proprietary Python-based research platform from scratch.
- Work directly with researchers to understand their methodology and pain points.
- Design a flexible, robust system supporting various research workflows.
Skills
How many opportunities will you get to develop a greenfield platform that directly shapes the future of a multi-billion-dollar prop trading business? I'd imagine this is one of few.
Here, you'll develop a proprietary Python-based research platform from scratch for one of the leading Quantitative Traders globally.
The challenge isn’t just performance or raw throughput - though both matter. It’s building a flexible, robust system capable of supporting a wide range of research workflows, each with its own quirks, data dependencies, and computational demands.
You won't just be writing clean, efficient Python, you'll be working directly with researchers to understand their methodology, tooling, and pain points. The system you help design will either accelerate the productivity of some of the smartest minds in quantitative finance - or get in their way.
There’s no single background that guarantees success here, but mastery of Python, a deep understanding of system design, and a collaborative mindset are non-negotiable. While most of the team comes from big-tech, there's space for exceptional buy-siders too.
Here, culture matters. This is a flat, collaborative team with no space for ego. They move fast, build carefully, and share success (and failures) together. If you're looking for a heads-down, siloed role, this isn't the right fit.
If you want to be involved from the beginning - shaping how this platform evolves from scratch - now is the time to reach out.
What they’re looking for:
- 2–10 years of experience in a high-performance, engineering-driven environment
- Advanced Python proficiency
- Experience designing and building complex, data-intensive systems
- Strong Linux fundamentals
- Excellent communication skills and a comfort working closely with non-engineering stakeholders
- Great to have: experience with containerization (e.g., Docker, K8,) and exposure to Golang
If this sounds interesting - or if you're simply curious to learn more - reach out for a conversation.
The team is actively hiring and will move quickly for the right person.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.