Description

You will architect and deploy end-to-end AI/ML solutions, from model design to scalable production endpoints.

This role is on-site.

Responsibilities

• Design, implement, and deploy supervised and unsupervised models, including neural networks (CNNs, RNNs, LSTMs).
• Develop and integrate solutions using LLMs and foundation models, applying prompt engineering and fine-tuning techniques (LoRA, PEFT).
• Manage the full model lifecycle, containerization (Docker, Kubernetes), and build scalable endpoints using FastAPI.
• Drive adoption of the Databricks platform to accelerate use case development and automation.
• Write efficient, maintainable Python code and build user-facing prototypes using Streamlit and front-end technologies.

Required Skills

• 5+ years of experience designing and deploying end-to-end AI/ML systems.
• Advanced proficiency in Python for machine learning, including scikit-learn, PyTorch, pandas, and NumPy.
• Deep expertise in Generative AI solutions using LLMs and foundation models, including fine-tuning experience.
• Proven experience with MLOps principles, Docker, and Kubernetes for deployment.
• Expertise in cloud platform deployment and infrastructure management (AWS and/or Azure).
• Strong functional knowledge of Databricks for data processing and platform management.
• Experience developing front-end tools using HTML, CSS, and JavaScript.

Key Skills

Education

Any Gradute