We are looking for a highly experienced GenAI Resource with a strong background in data science, machine learning, and AI architecture, specifically focusing on Natural Language Processing (NLP) and Large Language Models (LLMs). The ideal candidate will have extensive experience with Azure Cloud services and a proven track record in deploying AI models in production environments.
Responsibilities
- Design and implement AI solutions with a focus on NLP and LLMs, ensuring high performance and scalability.
- Manage end-to-end model production, from development to deployment and maintenance, using Azure services.
- Collaborate with cross-functional teams to gather requirements and develop AI-driven solutions.
- Develop, test, and deploy machine learning models using Python, leveraging libraries such as TensorFlow, PySpark, and Hugging Face Transformers.
- Create and manage large-scale data pipelines and batch processing workflows using Azure Databricks, and utilize Snowflake and SQL for data management.
- Apply advanced NLP techniques, including summarization, entity recognition, sentiment analysis, and text classification.
- Integrate external APIs into AI systems to enhance functionality and performance.
- Establish and maintain CI/CD processes for deploying and managing AI models in production environments.
- Provide technical guidance and support to offshore teams, ensuring project milestones and deliverables are met.
- Contribute to software product development and management when applicable.
Qualifications
- 15+ years in data science, machine learning, and AI architecture, with a specific focus on NLP and LLM models.
- Proven experience with Azure services, including Azure OpenAI, Azure Databricks, Azure DevOps, Azure Boards, and Azure App Services.
- Demonstrated end-to-end model deployment experience in Azure.
- Strong experience with Python and familiarity with AI/ML libraries such as TensorFlow, PySpark, Transformers, and FastAPI.
- Deep understanding of batch processing and large-scale data pipelines using Azure Databricks, with knowledge of Snowflake and SQL.
- Hands-on experience with LLMs, embedding models, and advanced NLP techniques.
- Familiarity with integrating external APIs into AI systems.
- Understanding of CI/CD practices for deploying and managing pipelines in production, including knowledge of Docker.