- Research and evaluate NLP, machine learning, deep learning, and Generative AI techniques, translating useful advances into practical solutions.
- Investigate ambiguous technical problems, form hypotheses, and run experiments comparing approaches.
- Design and build NLP, statistical ML, deep learning, and transformer-based solutions.
- Develop data pipelines, preprocessing, feature representations, embeddings, and training datasets for structured and unstructured data.
- Develop and evaluate LLM and GenAI solutions using prompting, RAG, embeddings, vector search, fine-tuning, agents, and structured generation.
- Design experiments, benchmarks, evaluation datasets, and statistical methods; lead error analysis and performance measurement.
- Deploy NLP and AI solutions to production, monitor them, and optimize their reliability and performance with engineering teams.
- Collaborate with engineering, product, and data science teams, and provide technical guidance and mentorship.
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