Key Responsibilities:
Design, develop, and deploy Generative AI models for text, image, or multimodal applications (e.g., LLMs, GPT, diffusion models, VAEs, GANs).
Build and fine-tune large language models (LLMs) using frameworks such as Hugging Face, LangChain, or OpenAI API.
Analyze complex datasets to derive insights, create predictive models, and develop AI-driven solutions.
Collaborate with cross-functional teams to identify use cases for GenAI across business domains (e.g., content generation, summarization, chatbots, recommendation systems).
Develop data pipelines and workflows to support scalable model training and evaluation.
Ensure data privacy, ethical AI practices, and compliance with organizational and regulatory standards.
Stay current with emerging research and technologies in Generative AI and contribute to internal capability building.
Required Skills & Qualifications:
Bachelor s or Master s degree in Computer Science, Data Science, AI/ML, Statistics, or a related field (PhD preferred).
3 8 years of experience in data science or machine learning roles.
Proficiency in Python, with experience using TensorFlow, PyTorch, or JAX.
Solid understanding of deep learning architectures (Transformers, CNNs, RNNs, autoencoders).
Experience working with Generative AI frameworks (OpenAI API, Hugging Face Transformers, LangChain, Stability AI, or similar).
Strong grounding in data preprocessing, feature engineering, and model evaluation.
Familiarity with cloud platforms (AWS, Azure, Google Cloud Platform) and MLOps tools (MLflow, Kubeflow, Docker).
Excellent communication skills and ability to translate technical concepts into business insights.
Preferred Qualifications:
Experience fine-tuning or training LLMs (e.g., GPT, LLaMA, Falcon, Mistral).
Knowledge of vector databases (Pinecone, FAISS, Chroma).
Exposure to RAG (Retrieval-Augmented Generation) pipelines.
Understanding of ethical AI principles and prompt engineering techniques.
Contributions to open-source AI projects or published research in GenAI.