Research Intern, Model Shaping (Fall 2026)
Quick Summary
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,
About the Role
~1 min readAs 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:
Responsibilities
~1 min read- →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
~1 min read- 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
- 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
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.
Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Mamba, FlexGen, SWARM Parallelism, Mixture of Agents, and RedPajama.
What We Offer
~1 min readWe 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.
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
Location & Eligibility
Listing Details
- Posted
- June 15, 2026
- First seen
- June 15, 2026
- Last seen
- June 15, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 67%
- Scored at
- June 15, 2026
Signal breakdown
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