Description

You will design, implement, and deploy advanced AI/ML solutions on cloud infrastructure.

This role is on-site.

Responsibilities

• Design and deploy supervised and unsupervised models, including regression, classification, and time-series forecasting.
• Develop and integrate solutions using LLMs and open-source foundation models, focusing on prompt engineering and fine-tuning.
• Manage the end-to-end model lifecycle, containerizing services with Docker and deploying via Kubernetes.
• Drive adoption of the Databricks platform to automate model development and create reusable solutions.
• Write efficient, maintainable Python code and build front-end prototypes using Streamlit and standard web technologies.

Required Skills

• 5+ years of experience designing and deploying end-to-end AI/ML systems.
• Advanced proficiency in Python, including core libraries like scikit-learn, PyTorch, pandas, and NumPy.
• Deep expertise in Generative AI, specifically LLM integration and fine-tuning techniques.
• Proven experience implementing MLOps pipelines using Docker and Kubernetes.
• Expertise in cloud deployment and infrastructure management on AWS and/or Azure.
• Strong functional knowledge of Databricks for AI/ML platform acceleration.
• Proficiency with Git for version control and software engineering best practices.
• Experience building user-facing applications using Streamlit, HTML, CSS, and JavaScript.

Key Skills

Education

Any Gradute