ML Research Intern
New York, San Francisco$15k/moFull-timePosted 2mo ago
About the role
PhD research intern role focusing on reinforcement learning, machine learning, and foundation models, with emphasis on large-scale model training, optimization, inference, long-context tasks, and improving robustness and efficiency in high-stakes deployments.
Responsibilities
- Join research team to develop and evaluate techniques for large-scale model training, optimization, and inference.
- Extend models to long-context and long-horizon tasks.
- Improve inference-time efficiency, reliability, and robustness in real-world deployments.
- Collaborate with research and engineering teams to translate ideas into working implementations.
Qualifications
- Currently pursuing a PhD in computer science, machine learning, or a related field.
- Demonstrated research in reinforcement learning, machine learning, foundation models, or related areas.
- Experience developing and evaluating large-scale models or machine learning systems.
- Familiarity with distributed training, large-scale inference, or multi-GPU environments.
- Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR.
- Strong programming and engineering skills, with the ability to translate research ideas into working implementations.
- Collaborative, mission-driven mindset and ability to work effectively across research and engineering teams.
Skills
Required:Reinforcement learningFoundation models (LLMs, multimodal models)
Nice to have:Distributed trainingModel inference optimizationResearch publication
Last updated Oct 21, 2026. Interested? Apply on the company site.
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