As a Quantitative Technologist, your goal is to enhance live trading systems, research infrastructure, and alpha generation through technology innovation.
We leverage cutting-edge software and hardware (mostly with modern C++) to push production level code daily and evolve fully-automated strategies, alpha generation processes, live trading systems, and machine learning research and simulation infrastructure used to analyze petabytes of data.
The Role
- Build and accelerate the firmwide AI ecosystem and infrastructure to support AI-native systems and tooling
- Identify workflow opportunities for developers and researchers to introduce AI-first systems and automation
- Design, deploy, and evaluate production-grade AI applications and advanced agentic workflows (utilizing RAG, semantic search, planning, and structured outputs)
- Develop platform-level safeguards, including bespoke evaluation harnesses, guardrails, approval workflows, tool-use limits, source attribution, and kill switches
- Optimize core metrics across agent systems, focusing on reasoning quality, retrieval accuracy, latency, cost, safety, and user experience
About You
- 5+ years of overall technical experience, including 2+ years of hands-on experience designing and building Generative AI/LLM applications in production
- Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Machine Learning, or a related technical field
- Strong proficiency in Python alongside solid software engineering principles and a deep understanding of the full AI/ML lifecycle (data prep through observability)
- Expert familiarity with agentic frameworks and modern AI orchestration and development tools (e.g., LangChain, LangGraph, AutoGen, LlamaIndex) alongside deep practical skills in prompt engineering
- Proven capability to evaluate and select foundational or open-weight models, balancing enterprise trade-offs across capability, context length, hosting, security, and cost
COMPENSATION – Competitive base salary, plus quarterly bonus based on individual performance and contribution towards success of others and the firm.
Skills Required
- 5+ years of overall technical experience
- 2+ years of hands-on experience designing and building production generative AI or LLM applications
- Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related technical field
- Strong proficiency in Python
- Strong software engineering principles
- Deep understanding of the full AI/ML lifecycle, from data preparation through observability
- Expert familiarity with agentic frameworks and AI orchestration tools such as LangChain, LangGraph, AutoGen, or LlamaIndex
- Practical prompt engineering skills
- Ability to evaluate and select foundational or open-weight models based on capability, context length, hosting, security, and cost
What We Do
Radix Trading is a privately funded proprietary trading and quantitative research firm. It develops technology-driven trading strategies using machine learning, statistical methodologies, and targeted collaboration, then monetizes that research through trading. The company employs research-driven strategies across major electronic markets and operates in Chicago, New York, and Amsterdam, with infrastructure supporting research, trading, exchange connectivity, hardware, and enterprise operations globally.
