Senior MQL5 + Python Quant Developer Needed – Institutional AI Trading Platform

I'm looking for a highly experienced quantitative developer (or small team) to build an institutional-grade algorithmic trading platform for MetaTrader 5 and Python.

This is not a simple Expert Advisor. It is a complete trading platform consisting of an MQL5 execution engine, Python AI research environment, machine learning pipeline, and real-time communication bridge.

The system is based on a four-tier quantitative architecture inspired by institutional trading firms.

The platform includes:

• MT5 Expert Advisor

• MT5 Indicator

• Python research and training environment

• ZeroMQ communication bridge

• Walk-forward analysis engine

• Machine learning training pipeline

• Portfolio and risk management

• Institutional dashboard

• Strategy Tester integration

Required experience with:

• MQL5 (Expert Advisors and Indicators)

• Python 3.11+

• NumPy

• Pandas

• Scikit-learn

• PyTorch

• Stable-Baselines3

• ZeroMQ

• SQLite

• Git

Experience with quantitative finance and machine learning is essential.

The platform must include:

MQL5

• Institutional Expert Advisor

• Institutional Indicator

• Multi-symbol support

• Multi-timeframe analysis

• Real-time feature computation

• Trade execution

• Position management

• Strategy Tester compatibility

• Dashboard

• Performance monitoring

Feature Engineering

Implement approximately 80+ quantitative features, including:

• Delta Flow

• Money Flow

• Volume Profile

• Multi-timeframe VWAP

• Market Structure

• Order Blocks

• Fair Value Gaps

• Liquidity

• Premium/Discount Zones

• Synthetic Level-2 Order Book

• Market Context Features

Machine Learning

Develop a complete machine learning pipeline with approximately 2,000 specialized models, including:

Tier 1

• Random Forest

• Extra Trees

• Gradient Boosting

• Logistic Regression

• Ridge

• KNN

• SVM

• Decision Trees

• AdaBoost

Tier 2

• Transformers

• Temporal Fusion Transformer (TFT)

• Temporal Convolutional Networks (TCN)

• Autoencoders

Tier 3

• PPO Reinforcement Learning

• DQN Reinforcement Learning

• Regime Switching RL

Tier 4

• Neural Meta-Ensemble

• Gating Network

• Attention Network

• Bayesian Uncertainty

• Regime Adapter

• Temporal Integrator

Implement an institutional seven-layer risk framework including:

• Fixed fractional sizing

• Kelly sizing (optional)

• Daily circuit breaker

• Equity protection

• Dynamic sizing after losses

• Breakeven

• ATR trailing stop

• Portfolio heat management

• Correlation management

• Hierarchical Risk Parity

Python environment should include:

• Feature engineering

• Training pipeline

• Walk-forward analysis

• Purged Cross Validation

• Combinatorial Purged CV (CPCV)

• Triple Barrier Method

• Meta-labeling

• Feature importance analysis

• Model registry

• Auto retraining

• Performance monitoring

Real-time communication between MT5 and Python using ZeroMQ with:

• Heartbeat

• Auto reconnect

• Low latency

• JSON messaging

The project should include:

• Complete MQL5 source code

• Complete Python source code

• MT5 Expert Advisor

• MT5 Indicator

• Documentation

• Configuration files

• Build instructions

• Strategy Tester support

• Deployment guide

• Git repository with clean commit history

The solution must be:

• Modular and object-oriented

• Well documented

• Easy to maintain and extend

• Optimized for performance

• Production-ready

• Cleanly structured

• Free from unnecessary hardcoded values

Looking for someone with proven experience in:

• Institutional algorithmic trading

• Quantitative finance

• Machine learning for trading

• MQL5 development

• Python AI development

• Financial data engineering

Please include in your proposal:

• Examples of similar projects

• GitHub profile (if available)

• Portfolio or previous work

• Screenshots or videos of trading systems you've built

• Relevant MQL5/Python source code samples (where permitted)

• Your proposed architecture for this project

• Estimated delivery timeline

• Fixed-price quotation

• Your experience with ZeroMQ, PyTorch, reinforcement learning, and MetaTrader 5

This is a large-scale software engineering project, comparable to building a professional quantitative trading platform rather than a standard Expert Advisor. Please apply only if you have strong experience with both MQL5 and Python-based quantitative systems.

I will not select a developer based only on a written proposal. Before I award this project, I expect you to demonstrate your capabilities. Please provide evidence of your experience through previous projects, portfolio links, GitHub repositories, screenshots, videos, code samples (where permitted), or any other relevant proof of your work.

In your proposal, explain how you would approach building this system, what parts you have implemented before, and why you are confident you can deliver a project of this complexity. Developers who cannot demonstrate relevant experience are unlikely to be shortlisted.

Please do not submit generic AI-generated proposals. I am looking for developers with genuine hands-on experience in building advanced MQL5 and Python quantitative trading systems.