ML & AI

Autonomous Trading Bot System

Built an autonomous multi-model trading system with a dry-run evaluation mechanism that dynamically switched to best-performing models — improving accuracy by 18% with zero downtime.

Role
ML Engineer
Duration
8 months
Client
Private Client

The Challenge

Financial markets are non-stationary — a model that works today may fail tomorrow. The client needed a system that could run multiple ML models in parallel and automatically switch to the best-performing one.

Approach & Solution

Developed a modular bot architecture where each bot encapsulates a different ML model (ANN, ARIMA, Prophet, ensemble methods). A supervisor module runs all models in dry-run mode, evaluates predictions against actual outcomes, and dynamically routes live capital to the best performer.

Results & Impact

  • Benchmarked 4+ ML model architectures in parallel
  • Dynamic model switching improved overall prediction accuracy by 18%
  • Zero-downtime model rotation with dry-run validation
  • Containerized AWS deployment with model versioning

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