Description

Key Skills: Python, GenAI, LangChain, Azure OpenAI, AWS SageMaker, RAG, Vector Databases, LLMs, Machine Learning, Prompt Engineering

Good to Have Skills: Solid foundation in ML algorithms, training pipelines and evaluation techniques. Familiarity with tokenization and model optimization. Hands-on with Azure cloud tools for model lifecycle, deployment and serverless execution. Ability to connect models to data sources, automation tools and orchestration platforms. Experience with Hugging Face, OpenAI, Pydantic, Pandas, Fast API, Numpy frameworks. Knowledge of embedding models, prompting techniques like zero shot, few shot, chain of thought.

Roles & Responsibilities:

• Build GenAI applications using Python for tasks like chatbots, summarization and intelligent automation.
• Develop and fine tune LLMs and ML models for classification, prediction, and decision support.
• Design solutions using embeddings, vector search, and retrieval augmented generation (RAG).
• Deploy models using Azure Machine Learning and Azure OpenAI scale with Azure Functions and Cognitive Services.
• Integrate models with AWS services like SageMaker, Lambda, Bedrock and data platforms like Snowflake.
• Integrate AI systems with APIs, enterprise data platforms and business workflows.
• Develop and design the architecture for AI systems, ensuring they integrate seamlessly with business operations.
• Choose appropriate technologies and tools for building and deploying generative AI solutions.
• Ensure the AI systems are scalable and can handle increasing workloads efficiently.
• Oversee the lifecycle of generative AI models, including development, deployment, and maintenance.
• Design and refine prompts used in natural language processing models to optimize performance.
• Integrate data from various sources to support AI model training and inference.
• Continuously monitor and optimize the performance of AI models and systems.
• Ensure AI systems adhere to security protocols and compliance standards.
• Work closely with data scientists, ML engineers, and other stakeholders to align AI solutions with business goals.
• Stay updated with the latest advancements in AI and incorporate innovative solutions into the architecture.

Experience Required: 5-10 years

Key Skills

Education

Any Graduate