Frontier Agents Intern
Research intern on the Agents team building and aligning frontier AI systems for complex agentic and scientific tasks. Focus on post-training methods, evaluation frameworks, self-learning, and scalable agent infrastructure.
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
- 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
- Fall internship program spans over 12 to 16 weeks
- Internship dates: September 14th to December 18th
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