Key / Primary Responsibilities:
- Lead cross-functional teams in the design, development, and deployment of Generative AI solutions, with a strong focus on Large Language Models (LLMs).
- Architect, train, and fine-tune state-of-the-art LLMs (e.g., GPT, BERT, T5) for various business applications, ensuring alignment with project goals.
- Deploy and scale LLM-based solutions, integrating them seamlessly into production environments and optimizing for performance and efficiency.
- Develop and maintain machine learning workflows and pipelines for training, evaluating, and deploying Generative AI models, using Python or R, and leveraging libraries like Hugging Face Transformers, TensorFlow, and PyTorch.
- Collaborate with product, data, and engineering teams to define and refine use cases for LLM applications such as conversational agents, content generation, and semantic search.
- Design and implement fine-tuning strategies to adapt pre-trained models to domain-specific tasks, ensuring high relevance and accuracy.
- Evaluate and optimize LLM performance, including handling challenges such as prompt engineering, inference time, and model bias.
- Manage and process large, unstructured datasets using SQL and NoSQL databases, ensuring smooth integration with AI models.
- Build and deploy AI-driven APIs and services, providing scalable access to LLM-based solutions.
- Use data visualization tools (e.g., Matplotlib, Seaborn, Tableau) to communicate AI model performance, insights, and results to non-technical stakeholders.
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