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
