Remote- full time- Posted July 29, 2026- via djinni.co
You will be redirected to djinni.co to apply.
About the project
Our client is a product company building an AI-driven trading and investing platform that covers equities, futures, forex and crypto. The team develops systematic strategies, portfolio models, copy-trading products and low-latency execution infrastructure.
What you'll do
- Research, build and maintain systematic trading strategies
- Develop backtesting, optimization and portfolio-construction frameworks
- Run walk-forward analysis, Monte Carlo simulations and other robustness checks
- Work with market data across equities, futures, forex and crypto
- Bring ML models into the research and signal-generation pipeline
- Move research into live trading together with the Java execution and platform teams
Track live strategy performance and improve risk-adjusted returns
Requirements
- 5+ years of production Python development
- Strong command of Pandas, Polars, NumPy
- Hands-on experience with at least one backtesting framework - VectorBT, Backtrader or QuantConnect LEAN
- Solid statistics and quantitative finance background
- Practical experience with portfolio optimization and risk management
- Trading experience in at least one asset class: futures, forex, equities or crypto
- PostgreSQL / TimescaleDB, cloud environments
Git, Docker, CI/CD
Nice to have
- ML stack: XGBoost, LightGBM, PyTorch
- FIX protocol
- Broker/venue integrations: Interactive Brokers, Alpaca, LMAX
- Java or C++ exposure
Background in institutional trading systems
What success looks like in the first year
- A pipeline producing 100+ validated strategy candidates
- Production-grade research infrastructure the whole team relies on
Measurably better portfolio Sharpe and lower drawdowns
We offer
- Competitive salary
- Fully remote work with a distributed international team
- A product role on a global AI trading platform, not outsourcing ticket work
