About Our Client

Our client is a rapidly expanding buy-side firm specializing in systematic trading across derivatives and cash markets. With a strong emphasis on AI-driven research, they integrate deep learning and reinforcement learning into high-frequency and medium-frequency trading strategies to generate uncorrelated returns for institutional investors.

The Opportunity

Join an elite research team at the forefront of AI-driven quantitative trading. This role focuses on applying state-of-the-art deep learning techniques to options, futures, and structured derivatives markets, with direct exposure to real-time alpha generation, portfolio optimization, and execution strategies. You will develop cutting-edge models for forecasting market dynamics and optimizing trade execution in a systematic, data-driven framework.

Key Responsibilities

• Develop advanced AI/Deep Learning models for predictive signal generation in derivatives markets (volatility surfaces, term structure forecasting, order flow dynamics).
• Apply reinforcement learning to optimize execution strategies, market making, and hedging frameworks.
• Build and refine NLP-based models for extracting signals from alternative datasets (news sentiment, earnings call transcripts, options order flow).
• Enhance systematic options trading strategies (e.g., delta-hedging, volatility arbitrage, statistical arbitrage) using deep learning-based predictive frameworks.
• Deploy and optimize AI models in production with real-time inference and model adaptation to changing market conditions.
• Improve research infrastructure (scalable data pipelines, high-performance backtesting engines, deep learning model training frameworks).
• Collaborate with portfolio managers and execution teams to integrate AI-driven signals into risk-managed trading portfolios.
• Publish internal research on deep learning architectures for financial time series forecasting, reinforcement learning for derivatives trading, and explainability of AI-driven strategies.

Ideal Candidate Profile

• 5+ years of experience in quantitative research, systematic trading, or AI-driven signal development at a top-tier hedge fund, prop firm, or high-frequency trading firm.
• Strong track record of alpha generation in derivatives markets (Sharpe ratio, risk-adjusted returns, and execution efficiency).
• Expertise in AI/Deep Learning frameworks: PyTorch, TensorFlow, JAX, or Hugging Face Transformers.
• Strong programming skills in Python and C++ (for low-latency research and execution).
• Advanced degree (PhD preferred) in AI, Machine Learning, Quantitative Finance, or Computational Sciences.
• Deep knowledge of:
  • Neural networks for time-series forecasting (LSTMs, Transformer models, CNNs for market data).
  • Reinforcement learning for execution optimization (Q-learning, PPO, AlphaZero-style models).
  • Generative models for synthetic data generation (GANs, VAEs, diffusion models).
  • Derivatives pricing models (stochastic volatility, Monte Carlo simulations, local volatility).
  • Market microstructure and high-frequency trading for listed options and futures.
  • Portfolio optimization under liquidity, margin, and regulatory constraints.

Why Join?

• Be a key player in an AI-first quantitative research team, working with top-tier hedge fund PMs and AI researchers.
• Work with exclusive datasets (tick-level options data, alternative data partnerships, deep order book data).
• Access to world-class compute resources for deep learning model training and high-performance AI-driven research.
• Remote-first culture with flexibility to work from anywhere, while engaging with top-tier talent in AI and systematic trading.