REAL-TIME ML SYSTEMS
Real-time ML architecture at Equinox AI
Low-latency inference, reinforcement-learning agents, and distributed backtesting for an algorithmic-trading platform.
The challenge
Connect real-time order-book and alternative-data feeds to dependable, low-latency model decisions.
My contribution
Set the platform architecture, combining online inference, Redis caching, Bayesian-updated RL agents, and distributed Monte Carlo backtesting. Introduced design reviews, runbooks, and Grafana observability.
The outcome
Delivered the architecture and operational foundations to the internal team, including statistical risk controls, automated kill switches, and hot-swap rollouts.
Areas of work
- Online inference
- Reinforcement learning
- Risk controls