Responsibilities:
- Build, deploy, and iterate on ML/NLP models and LLM-powered pipelines in production.
- Design embedding-based retrieval, ranking, and classification systems.
- Create evaluation frameworks to measure model and LLM output quality.
- Engineer features and labels from large-scale behavioral and text data.
- Run A/B experiments and tie model performance to business metrics.
- Work with product and engineering teams to turn business problems into ML solutions.
Requirements:
- 1 to 3 years of experience as a data scientist or ML engineer in a product or tech company.
- Strong Python and SQL skills.
- Hands-on experience with NLP and LLMs (prompting, embeddings, LLM pipelines, Gemini/OpenAI APIs).
- Experience shipping ML models to production.
- Solid ML and deep learning fundamentals (PyTorch or TensorFlow).
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