Research Intern, Model Shaping (Summer 2027)

Role Overview

Responsibilities

• Research and implement novel techniques in one or more Model Shaping focus areas.
• Design and conduct rigorous experiments to validate hypotheses.
• Document findings in scientific publications and blog posts.
• Integrate research results into Together AI products.

Focus Areas

• Focus areas include post-training through supervised learning, preference optimization, and reinforcement learning.
• Develop efficient neural-network training techniques, including distributed training, algorithmic improvements, and optimization methods.
• Perform robust and reliable evaluation of foundation-model capabilities.

Required Qualifications

• Be pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field.
• Have strong knowledge of machine learning and deep learning fundamentals.
• Have experience with deep learning frameworks such as PyTorch or JAX.
• Be familiar with Transformer architecture and recent developments in foundation models.

Preferred Qualifications

• Prior research experience training foundation models or in efficient machine learning is preferred.
• Publications at leading ML or NLP conferences are preferred.
• Understanding model optimization and hardware acceleration is preferred.
• Contributions to open-source machine learning projects are preferred.

Internship Program

• The internship runs 12 to 14 weeks.
• Summer 2027 cohort dates are May 17 to August 6 or June 14 to September 3.

Location

• The internship is based in the San Francisco or Amsterdam office.

Compensation

• The estimated US hourly rate is $58 to $70.
• Compensation is determined by location, level, role, experience, skills, and job-related knowledge.
• Housing stipends and other benefits are offered.