Stocks Trading Systems Engineer

QMetix, a stealth startup with a small, engineer-driven quantitative trading team, seeking a mid-level Trading Systems Engineer to be the primary lead developer responsible for the entire lifecycle of our systematic equity trading strategies. This is a high-autonomy role involving research, backtesting, deployment, and live trading with real capital across US, Asian, and potentially European markets. We are looking for an individual comfortable with fast iteration and direct ownership of production-ready systems.

We are a small stealth startup implementing systematic equity trading for a family office, focused on intraday and short/medium-horizon data. Our approach is engineering-centric, utilizing classical quantitative methods today with a near-term extension into machine learning where it enhances robustness and risk control. We offer minimal bureaucracy and long-term incentives, working directly with real capital.

As the primary developer, you will own the full strategy lifecycle: Research Backtest Validate Deploy Trade Live. You will work closely with the investment team, with light oversight from a senior engineer. The expectation is to deliver reliable, production-ready systems, with significant autonomy over technical design.

Location: Singapore, in-person (flexible hours)

This is a build, trade, fix, repeat role with real capital on the line, not an academic or research-only position.

• Build research, backtesting, and live trading systems for equity strategies
• Implement brokerage API execution (orders, positions, monitoring, fail-safes)
• Turn quantitative and ML ideas into production-ready code
• Enforce realistic backtests (costs, slippage, liquidity, regimes)
• Add guardrails for data quality, model stability, and execution safety

• 3+ years of software engineering experience, specifically in building financial markets systems.
• Proven, hands-on experience running live trading strategies.
• Python Engineering: High-quality code, clean architecture, testing, profiling, and packaging.
• Modeling: Proficiency in time-series modeling (ARIMA) and/or ML/DL techniques (e.g., Time series transformers, XGBoost, RNN/LSTM).
• Data Engineering: Experience with ETL/ELT, schema design, and data versioning.
• Validation & Backtesting: Expertise in walk-forward testing, rolling cross-validation (CV), leakage prevention, Monte Carlo simulation, tail risk analysis, and constraint checks.
• System Reliability & Reproducibility: Implementing config-driven runs, robust logging, artifact tracking, data checks, and model uncertainty gating.
• Market Knowledge: Practical understanding of financial markets (self-taught knowledge is acceptable, but a track record is required).
• Ownership: Comfortable owning systems end-to-end.