[Remote] Lead Quantitative Developer

Remote Full-time
Note: The job is a remote job and is open to candidates in USA. QSentia is building a next-generation hedge fund platform focused on AI-driven portfolio management. The Lead Quantitative Developer will design and implement advanced models for portfolio optimization and risk management, leveraging machine learning and quantitative finance expertise. Responsibilities β€’ Design and implement RL-based portfolio optimization models (e.g., DDPG, TD3, PPO) focused on adaptive risk management and regime detection β€’ Develop and integrate LLM-driven alpha signals, enabling the system to extract hidden insights from multimodal data sources (e.g., earnings calls, filings, news, social sentiment, market structure) β€’ Build systems that combine real-time alpha vectors with RL-driven portfolio allocation and trade execution β€’ Optimize performance for GPU-accelerated training and efficient data pipelines (SQL, cloud, or hybrid) Skills β€’ 1+ years of experience in quantitative development, algorithmic trading, or applied ML research in finance β€’ Strong background in machine learning / reinforcement learning (PyTorch, TensorFlow) applied to portfolio management or trading strategies β€’ Experience designing actor-critic RL frameworks (DDPG, TD3, PPO, SAC) with risk-adjusted reward functions β€’ Deep understanding of financial markets, risk models, and portfolio theory β€’ Proficiency in Python (NumPy, Pandas, PyTorch) and SQL/NoSQL databases; C++ or Rust is a plus β€’ Hands-on experience with LLMs (OpenAI, Claude, Gemini, etc.), NLP, or multimodal AI for financial signal extraction β€’ Proven ability to design backtesting engines and eliminate lookahead bias with point-in-time datasets β€’ Strong communication skills and ability to work with PMs, researchers, and technologists β€’ Experience with real-time market data APIs (Polygon, Bloomberg, Refinitiv, etc.) β€’ Knowledge of options markets and derivatives pricing β€’ Familiarity with distributed computing frameworks (Ray, Dask, Spark) for large-scale research β€’ Prior experience at a hedge fund, HFT shop, or asset manager in a quant dev or quant research role Benefits β€’ Equity only to start β€’ Equity + points in fund, with the potential for salary and bonus post-funding Company Overview β€’ Initial back test results: Sharpe: 2.6 Calmer: 5.6 Sortino: 5.5 Max DD: +18% It was founded in undefined, and is headquartered in , with a workforce of 2-10 employees. Its website is Apply tot his job
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