Applied AI Engineer (Summer Internship)

Description:

The Applied AI organization is a key part of BAM’s continued growth. Year over year, the knowledge needed to leverage data plays an increasingly important role in the firm’s core business. The analytical expertise that the AI organization provides the firm are part of BAM’s competitive advantage. Applied AI supports Investment Teams across all asset classes by providing research and tools powered by AI to help deliver results and PnL.

As an Applied AI Intern, you will go through a hands-on 10-week program and solve complex, real-world problems. You will experience firsthand how AI is used to enhance and support the investment process. Applied AI interns will be responsible for researching and implementing generative AI solutions to empower our investment teams to work more efficiently and effectively.

You’ll be involved in every phase of the analytics process, from research and idea generation to the hands-on development of systems to store, retrieve and derive insights from textual data. As part of the Applied AI team, you’ll get to see first-hand how AI can be used to enhance and support the investment process.

Qualifications:

Bachelor's or Master’s student graduating between December 2027 and May 2028 who is pursuing a degree Computer Science, Mathematics, Statistics, Data Science with a focus on Machine Learning and/or Generative AI techniques, or another related quantitative field.
Exceptional analytical, data processing and programming skills (at a minimum, python, numpy, pandas, scikit-learn, matplotlib and SQL)
Exceptional understanding of statistical and machine learning concepts
Familiarity with ETL tools and managing code repositories (GitHub)
Experience training and fine-tuning large language and embedding models, and using these to build applications (e.g. using LangChain)
Ability to clearly communicate complex and technical subject matters
Results driven mindset, ability to work in an ambiguous environment, and work collaboratively within a team environment
Experience with the following technologies is a plus: Vector Databases, OpenSearch, Apache Airflow, AWS, Spark, Databricks, Deep learning frameworks (e.g., Tensorflow, Keras and PyTorch)
AI research experience is a plus