About the Role
Youll build the learning system for autonomous trading agents enabling the fleet to learn from its own decisions and continuously improve.
This is a production ML role (not research) focused on reinforcement learning and closed-loop systems.
Key Responsibilities
Learning System & RL Loop
- Build feedback loop from trade outcomes strategy improvement
- Develop evaluation frameworks for signals and performance
- Automate strategy generation and backtesting
- Detect market regime shifts and adapt strategies
- Implement performance attribution systems
- Manage fleet coordination (risk capital allocation)
- Build telemetry/data infrastructure
Model & Inference
- Define and implement model hosting strategy
- Build domain-specific training pipelines
- Optimize inference for real-time trading agents
- Capture full decision telemetry across agents
Requirements
- Closed-loop production ML systems (non-negotiable)
- RL / online learning experience
- Full-stack ML ownership (data model production)
- Strong Python backend experience (Go/TS helpful)
- High-stakes system experience (preferred)
Bonus Skills
- Financial ML / trading systems
- LLM fine-tuning & serving
- Multi-agent systems
- DeFi / onchain experience
- Experience in sequential decision systems (robotics game AI etc.)
About the Role Youll build the learning system for autonomous trading agents enabling the fleet to learn from its own decisions and continuously improve. This is a production ML role (not research) focused on reinforcement learning and closed-loop systems. Key Responsibilities Learning System & RL ...
About the Role
Youll build the learning system for autonomous trading agents enabling the fleet to learn from its own decisions and continuously improve.
This is a production ML role (not research) focused on reinforcement learning and closed-loop systems.
Key Responsibilities
Learning System & RL Loop
- Build feedback loop from trade outcomes strategy improvement
- Develop evaluation frameworks for signals and performance
- Automate strategy generation and backtesting
- Detect market regime shifts and adapt strategies
- Implement performance attribution systems
- Manage fleet coordination (risk capital allocation)
- Build telemetry/data infrastructure
Model & Inference
- Define and implement model hosting strategy
- Build domain-specific training pipelines
- Optimize inference for real-time trading agents
- Capture full decision telemetry across agents
Requirements
- Closed-loop production ML systems (non-negotiable)
- RL / online learning experience
- Full-stack ML ownership (data model production)
- Strong Python backend experience (Go/TS helpful)
- High-stakes system experience (preferred)
Bonus Skills
- Financial ML / trading systems
- LLM fine-tuning & serving
- Multi-agent systems
- DeFi / onchain experience
- Experience in sequential decision systems (robotics game AI etc.)
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