Research Scientist Intern, MSL - Agentic Post-Training (PhD)

What you'll do

• Develop and iterate on agentic post-training methods and systems, including large-scale training runs.
• Improve the efficiency, scalability, and stability of training algorithms and deployed systems.
• Collaborate across teams and share research through publications, presentations, open-source releases, or model contributions.

What they ask for

• Currently pursuing or already hold a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a relevant technical field.
• Research experience in machine learning, deep learning, or natural language processing.
• Experience with deep learning frameworks such as PyTorch and programming languages such as Python, C++, C, or Java.
• Obtain and maintain work authorization in the country of employment; intend to return to the degree program after the internship.

Nice to have

• Research experience or publications in LLMs, foundation models, post-training, agentic AI, or reasoning/coding; experience with reinforcement learning and reward modeling.
• Experience with agentic systems, LLM evaluation, engineering, and cross-functional teamwork.

Pay

$7,650/month to $12,667/month (USD; monthly compensation; base salary or total pay not specified)

Tools

Muse, PyTorch, Python, C++, C, Java

AI focus

Agentic post-training of Muse foundation models, including supervised fine-tuning, reinforcement learning, evaluation, agentic task and environment creation, tool use, and long-horizon reasoning.