AI/ML Engineer and Data Scientist

As a Generative AI Developer/ AI Engineer/ML Engineer/Data Scientist at a Top IT MNC, you will be working remotely with 7 to 10 years of experience. You should be an immediate or early joiner possessing mandatory skills in AI Application Solution Design, LLM Application Frameworks, and Python. **Key Responsibilities:** - Deep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers) - Expert-level prompt engineering skills and experience implementing RAG patterns - Proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow) - Experience with RAG architectures, prompt engineering, fine-tuning, and distillation techniques - Usage of managed AI/ML services on the cloud platform (e.g., Azure Machine Learning Studio, AI Foundry) - Understanding of vector databases (e.g., Weaviate, Neo4j) - Familiarity with GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation) - Architecting and implementing scalable GenAI and Agentic AI solutions - Writing high-quality, production-ready Python code with strong testing and maintainability practices - Productionizing AI systems on Azure or AWS with enterprise-grade reliability and performance - Building and exposing APIs using FastAPI, integrating with databases through an ORM **Qualifications Required:** - Ability to understand clients business use cases and technical requirements and convert them into technical designs - Decision mapping and translation to developers - Identifying and narrowing down the best solution for clients requirements - Defining guidelines and benchmarks for NFR considerations - Writing and reviewing design documents for architecture, framework, and high-level design - Reviewing architecture and design for extensibility, scalability, security, design patterns, and user experience - Developing and designing solutions for defined functional and non-functional requirements Please note that this job requires expertise in AI technologies, proficiency in Python, and experience in implementing AI solutions. As a Generative AI Developer/ AI Engineer/ML Engineer/Data Scientist at a Top IT MNC, you will be working remotely with 7 to 10 years of experience. You should be an immediate or early joiner possessing mandatory skills in AI Application Solution Design, LLM Application Frameworks, and Python. **Key Responsibilities:** - Deep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers) - Expert-level prompt engineering skills and experience implementing RAG patterns - Proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow) - Experience with RAG architectures, prompt engineering, fine-tuning, and distillation techniques - Usage of managed AI/ML services on the cloud platform (e.g., Azure Machine Learning Studio, AI Foundry) - Understanding of vector databases (e.g., Weaviate, Neo4j) - Familiarity with GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation) - Architecting and implementing scalable GenAI and Agentic AI solutions - Writing high-quality, production-ready Python code with strong testing and maintainability practices - Productionizing AI systems on Azure or AWS with enterprise-grade reliability and performance - Building and exposing APIs using FastAPI, integrating with databases through an ORM **Qualifications Required:** - Ability to understand clients business use cases and technical requirements and convert them into technical designs - Decision mapping and translation to developers - Identifying and narrowing down the best solution for clients requirements - Defining guidelines and benchmarks for NFR considerations - Writing and reviewing design documents for architecture, framework, and high-level design - Reviewing architecture and design for extensibility, scalability, security, design patterns, and user experience - Developing and designing solutions for defined functional and non-functional requirements Please note that this job requires expertise in AI technologies, proficiency in Python, and experience in implementing AI solutions.