Machine Learning Research Intern (Winter/Spring 2027)
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Summary
On-site ML research internship (Winter/Spring 2027) in Sunnyvale focused on trust and safety in LLMs — prompt injections, safety alignment and guardrails, privacy, and interpretability — blending research with applied ML and software engineering in Python, PyTorch, Hugging Face/transformers, git, and AWS/GCP.
Role Overview
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.
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.
