Description

You design and implement end-to-end AI and machine learning solutions.

This role is on-site.

Responsibilities

• Design and deploy advanced supervised, unsupervised, and time-series models, including neural networks.
• Develop and integrate LLM and foundation model solutions, focusing on prompt engineering and fine-tuning.
• Manage the full model lifecycle, containerizing deployments with Docker and Kubernetes using FastAPI.
• Drive adoption of Databricks to automate ML workflows and accelerate use case development.
• Mentor junior engineers and establish governance standards for AI/ML practices.

Required Skills

• 10+ years of professional experience in AI/ML solution architecture.
• Advanced proficiency in Python and core ML libraries: PyTorch, Pandas, Polars, NumPy, Scikit-learn.
• Deep expertise in Generative AI, LLMs, and model fine-tuning techniques (e.g., LoRA).
• Proven experience deploying end-to-end ML systems using Docker and Kubernetes.
• Strong command of MLOps principles and version control using Git.
• Expertise in cloud platform deployment and infrastructure on AWS and/or Azure.

Preferred Skills

• Functional knowledge of Databricks for data processing and platform management.

Key Skills

Education

Any Graduate