Data Scientist

Role Overview: You will be responsible for developing and deploying generative AI models for text, image, audio, or video generation in the Retail domain. Your role will involve fine-tuning large language models (LLMs) and optimizing prompt engineering techniques to enhance model outputs. Additionally, you will work on building AI-driven chatbots, virtual assistants, and Agents using frameworks like TensorFlow, PyTorch, and Hugging Face Transformers. Key Responsibilities: - Design, develop, and deploy generative AI models for text, image, audio, or video generation. - Fine-tune large language models (LLMs) for specific use cases. - Develop and optimize prompt engineering techniques to improve model outputs. - Build AI-driven chatbots, virtual assistants, and Agents. - Train models using datasets and reinforcement learning techniques. - Deploy AI models using cloud services (AWS, GCP, Azure) or on-premises infrastructure. - Develop APIs and integrate AI models into applications. - Ensure model efficiency, scalability, and ethical AI compliance. Qualifications Required: - 3 to 9 years of experience in building Predictive AI and Generative AI solutions. - Proficiency in Python, TensorFlow, PyTorch, and Hugging Face libraries. - Strong knowledge of transformer models, LLM fine-tuning, and diffusion models. - Experience with LLM APIs (OpenAI, Anthropic, Mistral, etc.). - Understanding of prompt engineering, retrieval-augmented generation (RAG), and embeddings. - Knowledge of ML (Machine Learning), NLP (Natural Language Processing), and Computer Vision. - Experience in the Retail domain is preferred. - Familiarity with concepts of LLM is a plus. - Skills in Python, R, SQL, and Cloud technologies are desirable. Note: Retail projects you may work on include Customer segmentation, CRM, POS, Demand forecasting, Inventory Optimization, supply chain analytics, omnichannel retail strategies, and loyalty programs. Role Overview: You will be responsible for developing and deploying generative AI models for text, image, audio, or video generation in the Retail domain. Your role will involve fine-tuning large language models (LLMs) and optimizing prompt engineering techniques to enhance model outputs. Additionally, you will work on building AI-driven chatbots, virtual assistants, and Agents using frameworks like TensorFlow, PyTorch, and Hugging Face Transformers. Key Responsibilities: - Design, develop, and deploy generative AI models for text, image, audio, or video generation. - Fine-tune large language models (LLMs) for specific use cases. - Develop and optimize prompt engineering techniques to improve model outputs. - Build AI-driven chatbots, virtual assistants, and Agents. - Train models using datasets and reinforcement learning techniques. - Deploy AI models using cloud services (AWS, GCP, Azure) or on-premises infrastructure. - Develop APIs and integrate AI models into applications. - Ensure model efficiency, scalability, and ethical AI compliance. Qualifications Required: - 3 to 9 years of experience in building Predictive AI and Generative AI solutions. - Proficiency in Python, TensorFlow, PyTorch, and Hugging Face libraries. - Strong knowledge of transformer models, LLM fine-tuning, and diffusion models. - Experience with LLM APIs (OpenAI, Anthropic, Mistral, etc.). - Understanding of prompt engineering, retrieval-augmented generation (RAG), and embeddings. - Knowledge of ML (Machine Learning), NLP (Natural Language Processing), and Computer Vision. - Experience in the Retail domain is preferred. - Familiarity with concepts of LLM is a plus. - Skills in Python, R, SQL, and Cloud technologies are desirable. Note: Retail projects you may work on include Customer segmentation, CRM, POS, Demand forecasting, Inventory Optimization, supply chain analytics, omnichannel retail strategies, and loyalty programs.