Algorithmic Trading Software Engineer

Overview of the Team

MS Capital is a private fund management company with a strong founding team with long-accumulated experience in strategy modelling, trading system and platform development. Using advanced artificial intelligence technology as the cornerstone, and enforcing strict investment management, the company's investment fund has gained sustained and stable returns.

You will be joining MS Capital's technology arm, with AL/ML as its cornerstone, and is committed to providing users with high-quality and stable trading services. The company now has a number of experienced quantitative researchers, world-class deep learning scientists and engineers from leading internet companies and top universities including the Tsinghua University, National University of Singapore, Nanyang Technological University, Peking University, the Hong Kong University of Science and Technology, and other internationally renowned artificial intelligence academic institutions. The company has also provided various kinds of trading solutions for a number of leading brokerage firms and organisations. The company's vision is to integrate artificial intelligence technology with quantitative investment scenarios, relying on strong artificial intelligence R&D capabilities and advanced trading strategy models, to provide users with comprehensive and stable trading services.

Roles & Responsibilities:

• Design and optimize trading signals using deep learning algorithms.
• Research and develop market trading strategies utilizing deep learning techniques.
• Research and implement risk management strategies using deep learning models.
• Analyze trading logs and solve real-time trading issues.
• Deploy and optimize time series neural networks like LSTM and Transformer for prediction tasks.

Qualifications:

• Master's degree or above in Computer Science, Mathematics, or Physics.
• 3+ years of experience in software development using C++, C, Java, Python, or other high-level programming languages.
• Familiar with parallel computing frameworks such as Hadoop, Slurm, or Spark.
• Strong experience with deep neural networks, especially models like CNN, RNN, LSTM, and DRL.
• Hands-on experience with frameworks such as TensorFlow, PyTorch, or Caffe.
• Proficiency with at least one data analysis tool, such as MATLAB or R.
• Strong communication and learning skills with good English reading and writing proficiency.

Plus Points:

• Experience with big data for market model prediction and validation.
• Experience in reinforcement learning or time series forecasting.
• Participation in competitions like Kaggle, ILSVRC, or Tianchi.
• Self-driven with strong analytical abilities to solve real-time trading challenges.