Description:

Acorns is seeking a Machine Learning Intern to help shape and optimize their AI-powered coding environment.
The intern will work on cutting-edge machine learning applications that assist developers in writing better and faster code.
Responsibilities include developing and implementing Retrieval-Augmented Generation (RAG) models using Amazon Bedrock, exploring and integrating vector databases, and researching automated code generation tools.
The intern will analyze system performance metrics and collaborate with the team to refine Generative AI workflows.
This position is part-time, requiring 15-20 hours of work per week, and can be performed remotely within the United States or in the Irvine, CA office.
Candidates must be currently pursuing a Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Requirements:

Candidates must be currently pursuing a Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field (this is a hard requirement).
Familiarity with Generative AI concepts, RAG, and frameworks like Amazon Bedrock or similar is required.
Strong programming skills in Python or similar languages are necessary.
An understanding of system performance evaluation metrics and methodologies is expected.
Excellent written and verbal communication skills are essential.
Candidates should have a strong desire to deliver impactful products and possess exceptional drive and precision in their work.
An optimistic outlook on the potential for societal change is important.
Preferred qualifications include experience with Generative AI frameworks or libraries, knowledge of code generation tools, and research experience related to AI/ML system evaluation.

The position offers a competitive hourly wage of $30.00/hour.
Flexible work hours and location are provided, allowing for a remote-first work environment.
Interns will work with a talented and motivated team that is dedicated to the mission and values of Acorns.
The role presents a unique opportunity to contribute to meaningful work that addresses significant societal challenges.