Inference Systems Research Intern — ML & Systems

Together AI; San Francisco (CA); On-site; USD 80,000 - 96,000; Full time

Benefits offered by this job

Housing stipend

Competitive compensation

Job summary

Together AI in San Francisco invites a research intern to join the Inference Research team, focusing on distributed inference, compiler-aware optimization, and inference-time strategies for efficient foundation-model serving.

You will co-design cross-layer optimizations, run rigorous experiments, and publish findings while gaining exposure to CUDA, PyTorch, and large-scale ML systems within an AI-native cloud company.

Qualifications

• Currently pursuing a final year of Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Strong knowledge of ML and DL fundamentals.
• Experience with deep learning frameworks (PyTorch, JAX, etc.).
• Strong programming skills in Python.
• Familiarity with Transformer architectures and recent developments in foundation models.

Responsibilities

• Design and conduct rigorous experiments to validate hypotheses
• Communicate the plans, progress, and results of projects to the broader team
• Document findings in scientific publications and blog posts

Skills

Machine Learning fundamentals

Deep Learning basics

Python programming

Transformer models knowledge

Education

Bachelor's/Master/PhD in CS/EE or related field

Tools

CUDA programming

PyTorch

JAX

Open-source ML projects

Job description

Together AI in San Francisco invites a research intern to join the Inference Research team, focusing on distributed inference, compiler-aware optimization, and inference-time strategies for efficient foundation-model serving.

You will co-design cross-layer optimizations, run rigorous experiments, and publish findings while gaining exposure to CUDA, PyTorch, and large-scale ML systems within an AI-native cloud company.