SENIOR AI ENGINEER, QUANTITATIVE STRATEGIES

OneBullEx is a crypto futures exchange startup built for speed, reliability, and innovation. Our platform delivers real-time trading performance—even under extreme market volatility—powered by advanced automation and AI-driven tools, including our “300 Spartans” trading bots. With cutting-edge machine learning, a user-first design, and transparent risk management, we are on a mission to redefine how traders navigate the fast-moving world of digital assets.

JOB OVERVIEW

We are seeking a Senior AI Engineer, Quantitative Strategies to help pioneer a next-generation, self-evolving AI pipeline for trading strategy creation. This role goes beyond traditional engineering—you will architect an autonomous system that can generate, test, and refine its own strategies using the latest in large language models (LLMs) such as Gemini, ChatGPT, and Claude. If you are excited by the idea of making AI a true creative partner in quantitative trading, this is your chance to help shape the future of the industry.

CANDIDATE REQUIREMENTS

• Advanced degree (Master’s or Ph.D.) in Financial Engineering, Computer Science, Industrial Engineering, or a related quantitative field
• 3+ years of hands-on experience in quantitative or software engineering roles, ideally within trading, fintech, or financial markets
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and experience with ML frameworks (PyTorch, TensorFlow, or JAX)
• Solid knowledge of deep learning, reinforcement learning, and optimization techniques
• Experience with LLM APIs, prompt engineering, and preferably fine-tuning
• Strong software engineering fundamentals, including Git, testing, and deployment workflows
• Deep understanding of financial markets, statistical analysis, and strategy development principles

PREFERRED QUALIFICATIONS

• Proven track record of developing and executing trading strategies in live markets
• Recognition in quantitative competitions (e.g., Kaggle, Quantopian)
• GitHub or portfolio demonstrating complex, data-driven projects
• Experience with reinforcement learning or other adaptive systems
• A strong intellectual curiosity and drive to push technological boundaries

• Architect from the ground up an autonomous strategy generation and evaluation pipeline, making key technical decisions that will define its future
• Integrate and fine-tune cutting-edge LLMs to generate novel, testable trading hypotheses
• Build closed-loop feedback systems to automate backtesting, analyze performance, and iteratively improve AI-generated strategies
• Act as a bridge between quantitative research and AI engineering, working closely with traders and analysts to translate market insights into machine-executable strategies
• Ensure scalability, performance, and robustness of all deployed systems