Reinforcement Learning Specialist
Hong Kong
28-06-2024
Job Type
Permanent
Emp Type
Full Time
Industry
Financial Services
Salary Type
Annual
Salary
Negotiable
Job ID
32422
Job Description
This is the perfect role for you if:
- You are a creative and innovative problem-solver who wants to push the boundaries of what's possible in the dynamic world of cryptocurrency and fintech
- You thrive on end-to-end application development, from gathering requirements to delivering robust, production-ready solutions
- You are passionate about automating trading systems and related processes to maximize efficiency and minimize manual effort
- You are eager to continuously expand your knowledge in both financial concepts and cutting-edge machine learning techniques
Responsibilities:
- Design, develop, and refine advanced deep reinforcement learning models to power innovative trading and portfolio management applications
- Conduct in-depth research and experimentation to explore novel RL methods and uncover their potential applications in the financial markets
- Collaborate closely with the quantitative research team to seamlessly integrate RL models into existing trading strategies and infrastructure
- Optimize and fine-tune RL models to ensure peak performance, scalability, and resilience in live, production environments
- Stay at the forefront of the latest advancements in deep learning, reinforcement learning, and their practical applications in finance
Required Skills and Experience:
- Advanced degree (preferably a Ph.D.) in Computer Science, Machine Learning, Statistics, or a closely related quantitative field
- Extensive expertise and hands-on experience with deep reinforcement learning techniques, algorithms, and their underlying theoretical principles
- Proven track record of designing, implementing, and optimizing deep learning models using frameworks such as PyTorch, TensorFlow, or JAX
- Strong programming proficiency in Python, as well as experience with high-performance languages like C++ or Rust, and parallel computing
- Familiarity with quantitative finance concepts, financial data analysis, and trading system architectures is highly desirable
- Ability to conduct independent research and contribute to cutting-edge, innovative solutions