The Agents team investigates how to build, align, and scale frontier AI systems that can tackle complex, multi-step tasks and workflows across text and speech, with a particular focus on agentic and scientific domains. Our work sits at the intersection of agent capabilities, human-computer interaction, and infrastructure—from designing post-training methods for agentic behavior to developing evaluation frameworks for open-ended tasks where traditional metrics fall short.
As a research intern, you will work on problems at the frontier of agentic AI, where challenges in alignment, reliability, and scalability are deeply intertwined. Projects may involve developing new training recipes for self-learning and long-horizon reasoning, curating datasets for non-deterministic scientific and agentic tasks, studying failure modes in agentic behavior, or building infrastructure that enables agent operations at scale. You'll operate in a space where algorithmic innovation, dataset and interaction design, and systems work come together to push the boundaries of what AI agents can reliably accomplish.
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
Communicate the plans, progress, and results of projects to the broader team
Requirements
Currently pursuing a Masters or Ph.D. degree in Computer Science, Electrical Engineering, Information Science, or a related field
Publications at leading ML, NLP, or speech conferences or journals (such as NeurIPS, ICML, ICLR, *ACL, EMNLP, Interspeech)
Strong knowledge of Machine Learning and Deep Learning fundamentals
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Experience with deep learning frameworks (PyTorch, JAX, etc.)
Understanding of how LLMs work
Strong programming skills in Python
Familiarity with Transformer architectures and recent developments in foundation models
Example Research Directions
Training, developing, and evaluating frontier models, especially in the domain of agentic tasks and workflows
Designing and curating datasets for frontier agents alignment and post-training
Studying failure modes and developing safety paradigms for agentic behavior
Research new recipes (for RL or test time scaling) for self-learning and long-context tasks completion
Building agents that act on spoken input to carry out complex, multi-step tasks
Developing ML infrastructure that can power agent operations at scale
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.
About Together AI
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, Petals, Mixture of Agents, and RedPajama.
Compensation
We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 - $63 an hour. 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.
For more information about our privacy policy, please visit: https://www.together.ai/privacy
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