Machine Learning Research Intern (Winter/Spring 2027)

Role Overview

• prompt injections
• safety alignment and guardrails
• privacy and confidentiality
• interpretability

Expected Background: ML

• Research experience
  • Ability to pose relevant questions, find answers in existing literature or plan and execute experiments.
  • Ability to read and write research papers and technical articles.
  • PhD student or student at any level with research experience and peer-reviewed published work.

• Machine learning tools: pytorch, huggingface, transformers, datasets.

• Applied deep learning and LLM experience.
  • Training and evaluating deep models.
  • (nice to have) finetuning LLMs, multi-modal LLMs.

• (nice to have) Familiarity with ML[NLP,LLM,Vision] interpretability methods, sparse autoencoders, linear probes.

Expected Background: Software Engineering

• Development environments and tools:
  • unix, git, basic clouds usage on AWS and/or GCP
  • jupyter

• Programming:
  • python
  • (nice to have) “programming languages well-roundedness”
  • experience in statically-typed and functional languages

Compensation & Benefits

• Market aligned compensation for interns in the bay area.

Requirements

• Must be authorized to work in the USA or must be able to obtain CPT (Curricular Practical Training) approval from host university.
• The internship is expected to last at least 3 months and intersect most of the period starting from January, 2027 through end of March 2027.