Description

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

This role is on-site.

Responsibilities

• Design and implement supervised and unsupervised models, including neural networks (CNNs, RNNs, LSTMs).
• Develop and integrate solutions using LLMs and open-source foundation models, applying prompt engineering and fine-tuning (LoRA, PEFT).
• Manage the full model lifecycle, deploying scalable endpoints using Docker, Kubernetes, and FastAPI.
• Drive adoption of the Databricks platform to automate model development and create reusable solutions.
• Write maintainable Python code, enforce Git best practices, and build front-end prototypes using Streamlit.

Required Skills

• 5+ years of experience designing and deploying end-to-end AI/ML systems.
• Advanced proficiency in Python, including Scikit-learn, PyTorch, Pandas, NumPy, and Seaborn.
• Deep expertise in Generative AI, specifically fine-tuning LLMs and optimizing model performance/latency.
• Proven experience with MLOps principles using Docker and Kubernetes.
• Strong functional knowledge of Databricks for platform management and AI/ML acceleration.
• Experience building user-facing applications using Streamlit, HTML, CSS, and JavaScript.
• Expertise in cloud platform deployment and infrastructure management (AWS and/or Azure).
• Demonstrated systems thinking to translate business goals into scalable technical architectures.

Key Skills

Education

Any Gradute