Develop and improve NLP and generative AI solutions using prompt engineering, fine-tuning, retrieval-augmented generation, dataset preparation, model evaluation, experimentation, and optimization. Collaborate with AI Engineering teams, promote reproducibility, and progressively take on greater ownership while supporting continuous innovation.
Role Summary
Focus on NLP fundamentals, prompt engineering, dataset preparation, model evaluation, and supporting fine-tuning.
Build and improve NLP and Generative AI solutions through prompt engineering, fine-tuning, RAG, model evaluation, experimentation, optimization,
collaboration with AI Engineering teams, and continuous innovation. Ownership
increases progressively with experience.
Python, NLP, LLMs, HuggingFace, PyTorch, Prompt Engineering, RAG, Vector Databases, Docker, Linux, GPU-based training, and AI evaluation appropriate
to the experience level.
Scientific thinking, ownership, experimentation, collaboration, reproducibility, and continuous learning.
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