Machine Learning Research Intern (Summer 2027)

Scale AI · New York, NY; San Francisco, CA · University · listed October 19, 2026

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The shape of it

Seniority

Internship

Where

Hybrid

Stated pay

$120,000 – $150,000 USD

Requirements listed

Length

1,118 words

In the posting’s own words

As an intern, you'll work on a combination of deeply technical ML applications in production and cutting-edge research problems, with mentorship from world-class researchers and the opportunity to collaborate with leading teams across industry and academia. Interns own real, published or shipped work — not side projects.

What it asks for · 5

Create post-training or agentic solutions that integrate into our ability to deliver applications for enterprise and public sector clients
Currently enrolled in a BS, MS or PhD program with a focus on Machine Learning, Deep Learning, or Natural Language Processing, with a graduation date in Fall 2027 or Spring 2028
Prior research experience or a track record of publications on LLMs, NLP, multimodal models, agents, safety, evaluation, alignment, or a related field
Experience with one or more general purpose programming languages, including Python, Javascript, or similar
Hands-on experience with reinforcement learning, agentic systems, or evaluation infrastructure

Degree language

Currently enrolled in a BS, MS or PhD program with a focus on Machine Learning, Deep Learning, or Natural Language Processing, with a graduation date in Fall 2027 or Spring 2028

Tools and skills named

Models & research

Machine learning5×
NLP3×
Reinforcement learning3×
Deep learning2×
LLM

Languages

JavaScript
Python

Data

Data pipelines

Frameworks

Spring

Operations & finance

Excel

Ways of working

Mentorship

Words the posting leans on

models11×
learning9×
research9×
systems6×
data4×
evaluation4×
every4×
experience4×
machine learning4×
alignment3×
applications3×
capabilities3×
deliver3×
frontier models3×
government3×
internship3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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