Engineer Intern, GenAI Research – Summer Internship
Job Description:
- Design and implement a lightweight supervised fine tuning training pipeline using open source LLMs.
- Create new benchmarks to evaluate frontier models across defined scientific and performance criteria.
- Analyze production models to identify measurable areas for improvement.
- Improve model performance through targeted retraining and hyperparameter search.
- Deploy improved models while maintaining core model characteristics and avoiding regression.
- Build Python tooling to automate training, evaluation, benchmarking, and experimentation workflows.
- Implement structured evaluation methods, including rubric based scoring and LLM as a judge workflows.
- Document experimental design, benchmark methodology, and performance results with clarity and precision.
- Iterate rapidly in a research driven environment to increase model quality and reliability.
Requirements:
- Current enrollment in or recent completion of a Master’s or PhD in Computer Science, AI, Machine Learning, Computer Engineering, or a closely related technical field.
- Strong experience working with large language models, including supervised fine tuning, prompt engineering, or model evaluation.
- Hands on experience building machine learning pipelines or research infrastructure.
- Experience improving model performance through retraining or hyperparameter tuning.
- Proficiency in Python and comfort working with machine learning frameworks and open source model ecosystems.
- Familiarity with cloud environments such as AWS or Azure.
- Strong technical problem solving ability, including use of LLMs as development aids for building and iteration.
- Ability to work independently with minimal hand holding.
- Strong written communication skills for summarising research and drafting technical documentation.
- Ability to collaborate effectively in a remote research environment.
Benefits:
- Duration: June-August
- Schedule: Full-time
- Work Type: Remote
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