Research Intern, Model Shaping (Fall 2026)

Togetherai; San Francisco (CA); On-site; USD 79,900 - 86,788; Full time

Benefits offered by this job

Competitive compensation

Housing stipends

Opportunity to contribute to open-source projects

Job summary

Togetherai is looking for a Research Intern to join its Model Shaping team in San Francisco. The intern will research and implement novel machine learning techniques and design experiments to validate their findings.

Candidates should be pursuing a degree in a related field, with strong knowledge of machine learning fundamentals and experience using frameworks like PyTorch. The internship spans 12-16 weeks, offering competitive compensation and an opportunity to work with industry experts.

Qualifications

• Currently pursuing a relevant degree.
• Strong knowledge of Machine Learning and Deep Learning fundamentals is essential.
• Experience with deep learning frameworks like PyTorch or JAX is required.

Responsibilities

• Research and implement novel techniques in machine learning.
• Conduct rigorous experiments to validate hypotheses.
• Document findings in scientific publications.

Skills

Machine Learning fundamentals

Deep Learning fundamentals

Experience with deep learning frameworks

Familiarity with Transformer architecture

Education

Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or related field

Tools

PyTorch

JAX

Job description

About The Role

As a Research Intern in the Model Shaping team, you will work on one or more of the following areas:

• Advanced post-training methods across supervised learning, preference optimization, and reinforcement learning
• New techniques and systems for efficient training of neural networks (e.g., distributed training, algorithmic improvements, optimization methods)
• Robust and reliable evaluation of foundation model capabilities

The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems.

Past research led by Model Shaping interns resulted in the following publications:

• Escaping the Verifier: Learning to Reason via Demonstrations (ICML 2026)
• Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking (ICML 2026)
• FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models (ICLR 2026)

Responsibilities

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

Requirements

• Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a related field
• Strong knowledge of Machine Learning and Deep Learning fundamentals
• Experience with deep learning frameworks (PyTorch, JAX, etc.)
• Familiarity with the Transformer architecture and recent developments in foundation models

Preferred Requirements

• Prior research experience with training foundation models or efficient machine learning
• Publications at leading ML and NLP conferences (such as NeurIPS, ICML, ICLR, ACL, or EMNLP)
• Understanding of model optimization techniques and hardware acceleration approaches
• Contributions to open-source machine learning projects

Internship Program Details

Our fall internship program spans over 12 to 16 weeks where you’ll have the opportunity to work with industry-leading engineers building a cloud from the ground up and possibly contribute to influential open source projects. Our internship dates are September 14th to December 18th and this role will be located in our San Francisco or Amsterdam office.

Compensation

We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 to $63. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy