onsite
Machine Learning Scientist Intern - Recommendation Systems
ML Engineer
Internship focused on developing fair and high‑performance recommendation models using large language models and advanced NLP techniques. Ideal for PhD students with strong ML and fairness research experience.
About the role
Key Responsibilities
- Design, implement, and evaluate machine learning models for recommendation systems, emphasizing fairness and bias mitigation.
- Collaborate with cross‑functional teams to integrate large language models into recommendation pipelines.
- Conduct research on novel NLP techniques to improve content relevance and user experience.
- Analyze model performance, generate insights, and iterate on solutions to meet business objectives.
- Document experiments, share findings, and contribute to internal knowledge bases.
Requirements
- PhD candidate in Computer Science, Machine Learning, or related field with a focus on NLP or recommendation systems.
- Strong programming skills in Python and experience with PyTorch or TensorFlow.
- Proven track record of research on fairness, bias, or interpretability in ML models.
- Excellent analytical, problem‑solving, and communication skills.
Skills
machine learningnatural language processingpythonpytorch