Staff AI Engineer

Skills

About the Role

You will design and build production systems that convert trade outcomes into continuous learning and improved strategies. You will implement feedback loops, evaluation frameworks, automated strategy generation and backtesting, fleet monitoring and coordination, telemetry and data capture, model hosting and fine-tuning pipelines, and optimized inference for many concurrent agents.

Requirements

• Production ML engineering experience deploying and maintaining models that impact business outcomes
• Experience with reinforcement learning or online learning and learning from real-world outcomes
• Strong software engineering skills with Python as primary language; familiarity with Go or TypeScript
• Experience building data pipelines and distributed systems
• Proven experience closing the loop end-to-end where predictions drive actions that generate feedback and measurable improvement

Responsibilities

• Design and implement feedback loops that connect trade outcomes to strategy improvement
• Build evaluation frameworks to quantify which signals and configurations predict profitable trades
• Develop automated strategy generation and backtesting pipelines using fleet data
• Detect shifts in market conditions and adapt agent behavior accordingly
• Implement automated fleet monitoring for configuration errors, performance degradation, and infrastructure issues
• Perform performance attribution that decomposes trade drivers and feed insights back into strategy design
• Coordinate fleet-level risk management, capital allocation, and exploration versus exploitation
• Evaluate and implement model hosting and serving strategies, including proxied external models and on-prem domain models
• Build telemetry and data capture layers to structure every decision and outcome for learning
• Optimize inference pipelines for concurrent agents and cost-efficient production serving