Machine Learning Research Engineering Intern (Summer 2025)

The goal of the ML team at Scale is to develop machine learning solutions advancing the company mission. Our current focus areas are in Generative AI, working on LLMs, post-training, RLHF, safety and capabilities evaluations, scalable alignment, and synthetic data. You’ll be working on a combination of deeply technical ML applications in production and cutting-edge research problems. Working at Scale will give you opportunities to work with our wide customer base which includes leading research teams and exposure to a wide range of problems within machine learning.  

We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. Our machine learning models form the basis for Scale’s expansion and future product strategy.  We currently complete billions of tasks a month and will continue to grow to support more complex use cases and more advanced ML-powered products.

Example Projects:

• Research and develop machine learning solutions to assist humans in the loop.
• Aid in the creation of high quality ground truth data with speed and accuracy.
• Work with public Large Language models to benchmark and make custom versions for internal use cases.
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
• Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.
• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.
• Work with massive datasets to develop both generic models as well as fine tune models for specific products.

Required to have:

• Currently enrolled in a PhD Program with a focus on Machine Learning, Deep Learning, Computer Vision with a graduation date in Fall 2025 or Spring 2026
• Experience with one or more general purpose programming languages, including: Python, Javascript, or similar
• Ability to speak and write in English fluently
• Be available for a Summer 2025 (May/June starts) internship 

Ideally you’d have:

• Have had a previous internship around Machine Learning, Deep Learning, or Computer Vision
• Experience as a researcher, including internships, full-time, or at a lab
• Publications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to opensource projects