Offer summary

Qualifications:

Master’s or Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field with specialization in AI, Machine Learning, or Quantitative Finance., 5+ years of experience in AI/ML engineering, quantitative research, or trading technology, preferably in fintech or digital asset trading environments., Advanced proficiency in Python, R, and quantitative modeling; experience with C++ and cloud platforms is a plus., Strong understanding of blockchain data, digital asset markets, and market-neutral trading strategies..

Key responsibilities:

Lead the design, implementation, and deployment of AI/ML models to analyze large-scale blockchain and market data.

Collaborate with quantitative researchers, traders, and software engineers to integrate AI models into live trading systems.

Develop, automate, and maintain data pipelines and machine learning workflows for real-time and historical data analysis.

Research and prototype new market-neutral strategies leveraging statistical and machine learning techniques.

Job description

This is a remote position.

We are seeking an experienced AI Engineer with a strong fintech and quantitative research background to design, develop, and deploy advanced AI-driven solutions for our crypto trading operations. The ideal candidate will have a proven track record in machine learning, trading technology, and quantitative modeling, and will play a pivotal role in building robust, scalable systems that drive trading and investment decisions.

Key Responsibilities

• Lead the design, implementation, and deployment of AI/ML models to analyze large-scale blockchain and market data, enhancing trading strategies and risk management.

• Collaborate with quantitative researchers, traders, and software engineers to integrate AI models into live trading systems, ensuring optimal performance and reliability.

• Develop, automate, and maintain data pipelines and machine learning workflows for real-time and historical data analysis.

• Research and prototype new market-neutral strategies, leveraging statistical and machine learning techniques to identify alpha opportunities in digital asset markets.

• Contribute to the development of compliance, risk, and anti-money laundering (AML) systems using AI and data-driven approaches.

• Stay abreast of the latest advancements in AI, blockchain, and fintech, and proactively apply innovative solutions to complex trading challenges.

• Mentor junior engineers and foster best practices in AI/ML development within the team.

• Ensure all AI solutions comply with relevant Cayman Islands data privacy, AML, and financial regulations, and work closely with compliance teams to assess and mitigate AI-related risks.

Requirements

• Master’s or Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field with specialization in AI, Machine Learning, or Quantitative Finance.

• 5+ years of experience in AI/ML engineering, quantitative research, or trading technology, preferably in fintech or digital asset trading environments.

• Advanced proficiency in Python, R, and quantitative modeling; experience with C++ and cloud platforms (e.g., AWS, GCP, or Azure) is a plus.

• Demonstrated experience developing, deploying, and maintaining machine learning models in production trading systems.

• Strong understanding of blockchain data, digital asset markets, and market-neutral trading strategies.

• Excellent problem-solving skills, with the ability to design and implement innovative, data-driven solutions to complex trading and operational challenges.

• Effective communicator and collaborative team player, able to work cross-functionally with traders, quants, engineers, and compliance professionals.

• Technical writing skills and experience documenting models, systems, and research findings for internal and regulatory purposes.

Preferred Experience

• Prior experience in a crypto trading firm, hedge fund, or high-frequency trading environment.

• Familiarity with Cayman Islands fintech regulations, data privacy, and AML/CTF compliance requirements.

• Experience with cloud-based data infrastructure and distributed systems for large-scale data processing.