Python Professional -GenAI-LLMOps

Job description

Educational Requirements - Bachelor of Engineering, BTech, BCA, BSc, MTech, MSc, MCA Service Line - Data Analytics Unit Responsibilities - Key ResponsibilitiesDevelop and deploy Generative AI applications using LLMs (GPT, Llama, etc.) - Build and maintain LLM pipelines, including prompt engineering and fine-tuning - Design and implement end-to-end AI/ML workflows (data model deployment) - Work with vector databases for semantic search and retrieval (RAG architecture) - Implement LLMOps practices for monitoring, evaluation, and versioning - Integrate LLMs into applications via APIs and microservices - Optimize model performance, cost, and latency - Collaborate with data engineers, product teams, and stakeholders - Conduct testing, validation, and debugging of AI models - Ensure security, compliance, and responsible AI practices Additional Responsibilities - Experience with fine-tuning LLMs / parameter-efficient tuning (LoRA, PEFT) - Knowledge of multimodal AI (text, image, audio) - Exposure to cloud platforms (AWS, Azure, GCP) - Experience with Kubernetes and scalable deployments - Knowledge of data engineering tools (Spark, Kafka) - Familiarity with vector search optimization and embeddings - Understanding of AI governance, ethics, and compliance - Experience with chatbots, copilots, or conversational AI systems Technical and Professional Requirements - Primary skills:Technology- >Data Science- >Machine Learning, Technology- >Geographical Information System- >Spatial Databases- >SQL Server, Technology- >Machine Learning- >Python Preferred Skills - Technology- >AI-Data science- >PYTHON - Technology- >AI-Data science- >Machine Learning - Technology- >AI-Generative AI- >Generative AI - Basic- >retrieval augmented generation (rag)