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About the role
Key Skills & Expertise: - Generative AI & LLMs: Proficiency in GPT-3, Langchain, and LLMs with experience in prompt engineering, few-shot/zero-shot learning, RLHF, and model optimization. - Machine Learning & NLP: Strong experience in Python with deep learning frameworks like Hugging Face, TensorFlow, Keras, and PyTorch. Solid understanding of embeddings and data modeling. - Databases: Experience with vector databases, RDBMS, MongoDB, NoSQL databases (HBase, Elasticsearch), and data integration from multiple sources. - Software Engineering: Expertise in data structures, algorithms, system architecture, and distributed systems. - Platform & Cloud: Hands-on experience with Kubernetes, Spark ML, Databricks, and developing scalable platforms at scale. - API Development: Proficiency in API design, RESTful services, and data mapping to schemas. Key Responsibilities: - Design, develop, and implement generative AI models using GPT, VAE, and GANs. - Optimize LLM performance through fine-tuning, hyperparameter evaluation, and model interpretability. - Collaborate with ML and integration teams to integrate AI models into scalable web applications. - Build and maintain distributed systems with robust system architecture. - Integrate data from diverse sources and design productive APIs for seamless functionality. - Enhance response quality and performance using RLHF and other advanced techniques. Educational Qualifications & Requirements: - B.Tech / B.E. /M.Tech / M.E. - Proven track record in building and deploying AI/ML models, particularly LLMs. - Prior experience developing public cloud services or open-source ML software is a plus. - Knowledge of big-data tools would be a big plus .
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