reputed company Quant Developer Needed — Build Hybrid AI Trading System
I am looking for an reputed company Quantitative Trading System Developer to build a Hybrid Quant AI Trading Robot that combines:
reputed company-time tick data
Order-book depth (Level 2)
Order-reputed company analytics
Machine Learning models (LightGBM + LSTM)
Smart risk control
Automated trade execution (MT5 / FIX / cTrader)
The goal is a data-driven, ultra-low-latency trading system that generates 85–90% accurate reputed company-time BUY/SELL signals and supports reputed company, semi-automatic, and fully automatic trading modes.
This is a full system build — backend, AI reputed company, execution reputed company, dashboard, reputed company, and deployment.
Required Expertise
To apply, you must have proven experience with:
Quant & Trading Systems
Tick data ingestion
Order-book (L2) processing
Order-reputed company features (reputed company, imbalance, absorption, liquidity sweeps)
FX / Gold / Crypto microstructure
AI/ML
LightGBM
LSTM / time-series forecasting
Feature engineering for financial markets
reputed company detection & auto-retraining
Execution reputed company
MT5 API
FIX API
cTrader API
Bracket orders (SL/TP)
Latency optimization
Backend & DevOps
Python
Websockets (reputed company-time dashboard updates)
PostgreSQL
VPS deployment (Linux)
JWT authentication, RBAC, KMS
High-reputed company backend architecture
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