Role overview
- Direct influence on how professional investors make decisions
- Hard problems at the edge of AI, data, and finance
- Real ownership and technical autonomy
- Senior peers who care about quality and outcomes
What you'll work on
- Design, fine-tune, and deploy ML and LLM-driven systems used in production by professional investors
- Build and maintain inference pipelines that are fast, observable, and reliable
- Integrate OpenAI, Gemini, and Anthropic models into reasoning and knowledge systems
- Work closely with backend engineers to productionize models in Golang-based services
- Improve signal quality, not just model accuracy
- Review code and designs with a bias toward long-term maintainability
Tags & focus areas
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