Research Intern, Inference
Research intern on the Inference team building efficient serving systems for large foundation models. Focus on distributed inference, compiler-aware optimization, and novel inference-time strategies.
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
Requirements
- Currently pursuing a final year of Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or a 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 Qualifications
- Prior research experience in foundation models, efficient machine learning, or ML systems
- Publications at leading conferences in machine learning or systems (i.e., MLSys, ICLR)
- Experience with CUDA programming (for kernel development)
- Understanding of model optimization techniques and hardware acceleration approaches
- Contributions to open-source machine learning projects
Internship Program Details
- Fall internship program spans 12 to 16 weeks
- Dates: September 14th to December 18th
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