Python and familiar with AI/Gen AI frameworks. Experience with data manipulation libraries like Pandas and NumPy is crucial.
Specific expertise in implementing and managing large language models (LLMs) is a must.
Fast API experience for API development
A solid grasp of software engineering principles, including version control (Git), continuous integration and continuous deployment (CI/CD) practices, and automated testing, is required. Experience in MLOps, ML engineering, and Data Science, with a proven track record of developing and maintaining AI solutions, is essential.
We also need proficiency in DevOps tools such as Docker, Kubernetes, Jenkins, and Terraform, along with advanced CI/CD practices.
Experience Agentic AI implementation
Job Classification
Industry: Emerging Technologies (AI/ML)Functional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Full Stack Data ScientistEmployement Type: Full time