Machine Learning Research Intern; Winter

This internship is focused on ML research mixed with applied ML and software engineering. Topic of the internship is around trust and safety in LLMs such as:

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

Other topics closer aligned with the student's research may be considered.

• 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)
    fine tuning LLMs, multi-modal LLMs.

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

• 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

• Market aligned compensation for interns in the bay area.

• 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.