Job Description
Jain Global is a global multi-strategy hedge fund which began trading in 2024, with offices in New York, Houston, London, Hong Kong, and Singapore. We operate across Macro, Fundamental Equities, Equity Arbitrage, Systematic, Credit, and Commodities, with APAC as a regional multi-strategy platform. Our teams combine rigorous research, technology, and engineering across a broad range of domains and workflows.
We are hiring AI Research Interns to build and evaluate AI-driven systems and applications across a variety of domains. The role focuses on implementing, extending, and stress-testing modern AI systems, including LLMs and agent-based frameworks, in practical real-world settings.
You will work closely with researchers and developers on implementation-heavy projects involving unstructured data processing, workflow automation, experimentation, and evaluation of LLM-based systems for practical research and engineering use cases.
The work is highly iterative and hands-on. Typical tasks include developing pipelines, analysing model behaviour, debugging failure modes, extending open-source frameworks, and evaluating robustness through testing and statistical analysis.
Example Areas Include
- Implementing and extending AI agent workflows and automation systems
- Structuring, normalizing, and querying unstructured datasets (documents, reports, text)
- Extending and adapting open-source AI frameworks to internal use cases
- Prototyping research and data-processing tools
- Evaluating model outputs for robustness, consistency, and practical usefulness
Responsibilities
- Design, build, and iterate on AI-driven systems and workflows
- Implement LLM pipelines, agent architectures, and supporting infrastructure
- Extend and modify existing open-source frameworks where appropriate
- Design and run experiments to evaluate robustness and real-world applicability
- Work with structured and unstructured datasets
Background & Essential Qualifications
- Currently pursuing (or recently completed) a Bachelor's, Master's, or PhD in:
- Computer Science, AI/ML, Mathematics, Statistics, Engineering
- Quantitative Finance, or Finance with strong technical depth and interest in AI
- Strong programming ability in one or more of Python, C++, Java, etc.
- Experience building and modifying systems involving LLMs, AI agents, or related technologies
- Familiarity with software development fundamentals, including:
- Data handling and storage (e.g., SQL, databases, data pipelines)
- Writing maintainable, modular code
- Version control and collaborative development workflows
- Strong problem-solving and analytical skills
Preferences
- Familiarity with quantitative research, financial markets, or research-driven environments such as hedge funds or trading firms
- Familiarity with structured financial, market, or time-series datasets
