Data Scientist Gen AI- Offshore

Job Description Job Description: As a Data Scientist - GenAI at our company, your role will involve leading the development and deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for various enterprise use cases. You will be responsible for designing and building Generative AI solutions using Large Language Models (LLMs) for business problems across domains like customer service, document automation, summarization, and knowledge retrieval. Additionally, you will collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs, while staying updated with the latest trends in LLMs, transformers, and GenAI architecture. Key Responsibilities: - Design and build Generative AI solutions using Large Language Models (LLMs) for various business problems. - Fine-tune or adapt foundation models using domain-specific data. - Implement RAG pipelines, embedding models, and vector databases. - Collaborate with cross-functional teams to build AI applications and APIs. - Develop custom prompts and prompt chains for AI solutions. - Evaluate model performance and optimize accuracy, latency, and cost. - Stay up to date with the latest trends in LLMs, transformers, and GenAI architecture. Qualifications: - 5+ years of experience in Data Science / ML, with 1+ year hands-on experience in LLMs / GenAI projects. - Strong Python programming skills, especially in libraries like Transformers, LangChain, scikit-learn, PyTorch, or TensorFlow. - Proficiency in OpenAI (GPT-4), Claude, Mistral, LLaMA, or similar models. - Knowledge of vector search, embedding models (e.g., BERT, Sentence Transformers), and semantic search techniques. - Ability to build scalable AI workflows and deploy them via APIs or web apps. - Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices. - Excellent communication skills with the ability to translate technical solutions into business impact. Preferred Qualifications: - Experience with prompt tuning, few-shot learning, or LoRA-based fine-tuning. - Knowledge of data privacy and security considerations in GenAI applications. - Familiarity with enterprise architecture, SDLC, or building GenAI use cases in regulated domains such as finance, insurance, healthcare. Job Description: As a Data Scientist - GenAI at our company, your role will involve leading the development and deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for various enterprise use cases. You will be responsible for designing and building Generative AI solutions using Large Language Models (LLMs) for business problems across domains like customer service, document automation, summarization, and knowledge retrieval. Additionally, you will collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs, while staying updated with the latest trends in LLMs, transformers, and GenAI architecture. Key Responsibilities: - Design and build Generative AI solutions using Large Language Models (LLMs) for various business problems. - Fine-tune or adapt foundation models using domain-specific data. - Implement RAG pipelines, embedding models, and vector databases. - Collaborate with cross-functional teams to build AI applications and APIs. - Develop custom prompts and prompt chains for AI solutions. - Evaluate model performance and optimize accuracy, latency, and cost. - Stay up to date with the latest trends in LLMs, transformers, and GenAI architecture. Qualifications: - 5+ years of experience in Data Science / ML, with 1+ year hands-on experience in LLMs / GenAI projects. - Strong Python programming skills, especially in libraries like Transformers, LangChain, scikit-learn, PyTorch, or TensorFlow. - Proficiency in OpenAI (GPT-4), Claude, Mistral, LLaMA, or similar models. - Knowledge of vector search, embedding models (e.g., BERT, Sentence Transformers), and semantic search techniques. - Ability to build scalable AI workflows and deploy them via APIs or web apps. - Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices. - Excellent communication skills with the ability to translate technical solutions into business impact. Preferred Qualifications: - Experience with prompt tuning, few-shot learning, or LoRA-based fine-tuning. - Knowledge of data privacy and security considerations in GenAI applications. - Familiarity with enterprise architecture, SDLC, or building GenAI use cases in regulated domains such as finance, insurance, healthcare.