AI Engineering Intern - 6 months

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AI Engineering Intern - 6 months

Location:

Singapore, SG

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We are one of the largest global private markets investment managers, serving over 800 institutional investors worldwide. We have USD 185 billion in assets under management and around 2,000 professionals across 24 offices worldwide. Partners Group is an equal opportunity employer committed to cultural diversity.

What it's about

As an AI Engineering Intern in our AI Pods, you'll get hands-on experience working alongside experienced engineers at the heart of the business, helping to explore, prototype, and deliver real AI solutions. You'll contribute to building LLM-powered products—learning how ideas move from discovery to first value, and how successful solutions are scaled through reusable components and strong governance over trusted, AI-ready data. What makes this internship exciting is the mix of real business exposure and advanced applied AI (RAG, agents, extraction, evaluation), all within a highly collaborative, agile environment where responsible AI, data governance, and risk controls are part of everyday practice from day one.

Key responsibilities

Support the team in identifying and exploring potential AI use cases, including basic research to inform buy-vs-build discussions.

Assist in designing and delivering AI prototypes, contributing across problem definition, experimentation, and pilot stages.

Help build AI-powered features and components under the guidance of senior engineers.

Contribute to the development of datasets, retrieval pipelines, and reasoning workflows across different business functionalities.

Explore integrations with vendor AI platforms and internal AI solutions, learning to reuse existing capabilities where possible.

Help instrument solutions to track adoption, quality, and performance metrics.

Collaborate with the technology team to learn how secure, compliant, and supportable solutions are built.

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What we expect

Currently pursuing or recently completed a Bachelor's in Computer Science, Data Science, Artificial Intelligence / Machine Learning, Software Engineering, or a related discipline.

Interest in the financial industry and a curiosity to learn about financial markets (prior exposure is a plus, not a requirement).

Some practical experience with ML/AI concepts through coursework, personal projects, hackathons, internships, or open-source contributions.

Awareness of cloud platforms (AWS preferred); any AWS learning paths or certifications are a plus.

Working proficiency in a modern programming language, ideally Python.

Familiarity with databases such as PostgreSQL, MS SQL, Snowflake, or similar—through coursework or projects.

Foundational understanding of how to build software applications (e.g., Python, APIs, basic system integration, testing).

Exposure to teamwork on software projects, with an appreciation for code quality, good design, and collaboration.

Familiarity with the software development lifecycle, version control (e.g., Git), and an interest in modern DevOps practices.

Ability to break down ambiguous problems into smaller tasks and communicate progress clearly.

Awareness of the importance of working responsibly with sensitive/confidential data, and a willingness to learn about governance, risk, and security practices.

Strong collaboration and communication