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Machine Learning Research Engineering Intern (Summer 2025)

  • Internship
    Full-time
    Summer Internship
  • Data
    Research & Development
  • San Francisco

AI generated summary

  • You must be a PhD student in ML/Deep Learning/Computer Vision graduating Fall 2025 or Spring 2026, proficient in Python/Javascript, available Summer 2025, and fluent in English.
  • You will research and develop machine learning solutions, improve existing models, benchmark language models, create high-quality data, and collaborate on product enhancements using large datasets.

Requirements

  • 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

Responsibilities

  • - 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.

FAQs

What is the focus of the ML team at Scale?

The ML team at Scale focuses on developing machine learning solutions in areas such as Generative AI, LLMs, post-training, RLHF, safety evaluations, scalable alignment, and synthetic data.

What type of projects will I be working on during the internship?

Interns will work on a variety of projects including developing machine learning solutions for human-in-the-loop systems, creating high-quality ground truth data, benchmarking and customizing public Large Language models, deploying and improving state-of-the-art models, and working with large datasets for model development.

What qualifications are required for this internship?

Candidates should be currently enrolled in a PhD program focused on Machine Learning, Deep Learning, or Computer Vision, with a graduation date in Fall 2025 or Spring 2026. Experience with programming languages like Python or JavaScript and fluency in English are also required.

Is prior internship experience required?

While not strictly required, having previous internship experience in Machine Learning, Deep Learning, or Computer Vision is ideal for candidates.

When does the internship start?

The internship is set to start in Summer 2025, specifically in May or June.

What type of work environment does Scale promote?

Scale promotes an inclusive and equal-opportunity work environment, committed to being an affirmative action employer.

Is research experience valued for this position?

Yes, having experience as a researcher, including internships or contributions to top-tier journals, is considered beneficial for candidates.

Are there any opportunities for advancement or full-time positions after the internship?

While the job description does not specify this, internships often serve as a pathway to full-time positions within the company, depending on performance and business needs.

Do you support employees with disabilities?

Yes, Scale is committed to providing reasonable accommodations for applicants with physical and mental disabilities during the application and recruitment process.

What kind of companies does Scale collaborate with?

Scale collaborates with a range of entities including generative AI companies like OpenAI and Meta, government agencies like the U.S. Army and Air Force, and enterprises like GM and Accenture.

The Data Platform for AI: High quality training and validation data for AI applications.

Technology
Industry
201-500
Employees
2016
Founded Year

Mission & Purpose

At Scale, our mission is to accelerate the development of AI applications. We believe that to make the best models, you need the best data. The Scale Generative AI Platform leverages your enterprise data to customize powerful base generative models to safely unlock the value of AI. The Scale Data Engine consists of all the tools and features you need to collect, curate and annotate high-quality data, in addition to robust tools to evaluate and optimize your models. Scale powers the most advanced LLMs and generative models in the world through world-class RLHF, data generation, model evaluation, safety, and alignment. Scale is trusted by leading technology companies like Microsoft and Meta, enterprises like Fox and Accenture, Generative AI companies like Open AI and Cohere, U.S. Government Agencies like the U.S. Army and the U.S. Airforce, and Startups like Brex and OpenSea.