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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, collaborate with the team to refine Generative AI workflows, and improve developer adoption of AI-generated code.
This is a part-time remote position, expected to work 15-20 hours per week, with optional access to office space in Irvine, CA.
Requirements:
Candidates must be currently pursuing a Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
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 essential.
Excellent written and verbal communication skills are required.
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.
Benefits:
The position offers a competitive hourly wage of $30.00/hour.
Flexible work hours and location are provided to accommodate the intern's schedule.
Interns will work with a talented and motivated team that values collaboration and care for one another and the mission.
The role presents a unique opportunity to contribute to meaningful work that addresses significant societal challenges.
Apply now
Please, let Acorns know you found this job
on RemoteYeah
.
This helps us grow 🌱.