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Tech Stack
Tools & technologiesDistributed SystemsGoPythonTypeScript
About the role
Key responsibilities & impact- Build feedback loops from outcomes → strategy improvements (signals, risk, timing)
- Develop evaluation frameworks to identify what drives profitable trades
- Automate strategy generation, backtesting, and deployment
- Design multi-agent learning and fleet coordination systems
- Own ML/LLM systems end-to-end: data → model → production → measurable impact
Requirements
What you’ll need- Proven ML engineering experience in production environments
- Background in reinforcement learning or online learning (closed-loop systems)
- Strong programming skills (Python required; Go/TypeScript is a plus)
- Experience building data pipelines and distributed systems
- Nice to have: fintech/trading, LLM fine-tuning, multi-agent systems
Benefits
Comp & perks- Total compensation: ~$450K+
- Base: $175K–$250K
- Equity + token upside
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningreinforcement learningonline learningPythonGoTypeScriptdata pipelinesdistributed systemsbacktestingmulti-agent systems
Soft Skills
strategic thinkingproblem-solvingcommunicationcollaborationanalytical skills
