Inference Systems Research Intern – Summer 2027

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

Benefits offered by this job

Housing stipend

Competitive compensation

Job summary

Together AI, the AI Native Cloud, invites a Research Intern, Inference, for Summer 2027 in San Francisco. You will explore distributed inference, compiler-aware optimization, and novel inference-time strategies, contributing to scalable, efficient serving architectures for large foundation models.

You will design experiments, collaborate across teams, and document findings for publications and blogs. This internship emphasizes hands-on research across ML, systems, and hardware optimization.

Qualifications

• Pursuing a final year of Bachelor's, Master's, or Ph.D. in CS, EE, or related field.
• Strong knowledge of Machine Learning and Deep Learning fundamentals.
• Experience with deep learning frameworks (PyTorch, JAX, etc.).
• Strong programming skills in Python.
• Familiarity with Transformer architectures and recent developments in foundation models.
• Preferred: research in foundation models, efficient ML, or ML systems.

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

Deep Learning

Python

PyTorch

JAX

Transformer architectures

Foundation models

Education

Bachelor's/Master's/PhD in Computer Science, Electrical Engineering, or related field

Final-year student

Tools

CUDA programming

Open-source contributions

Job description

Together AI, the AI Native Cloud, invites a Research Intern, Inference, for Summer 2027 in San Francisco. You will explore distributed inference, compiler-aware optimization, and novel inference-time strategies, contributing to scalable, efficient serving architectures for large foundation models.

You will design experiments, collaborate across teams, and document findings for publications and blogs. This internship emphasizes hands-on research across ML, systems, and hardware optimization.