ML Research Intern

Stack

Responsibilities

• ▹Improve existing methods and develop new 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 high-stakes real-world deployments

Requirements

• ▹Currently pursuing a PhD in computer science, machine learning, or a related field
• ▹A demonstrated record of research in reinforcement learning, machine learning, or foundation models
• ▹Experience developing and evaluating large-scale models or machine learning systems
• ▹Strong programming and engineering skills, translating research ideas into working implementations

Nice to have

• ▹Familiarity with distributed training, large-scale inference, or multi-GPU environments
• ▹Publications at leading venues (NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, TMLR)

Soft skills

About the company

Modal is building the new infrastructure layer for the AI era, providing instant GPU access, sub-second container starts, and native storage. The company raised a $355M Series C at a $4.65B valuation and has crossed $300M+ ARR.