Description

You will design and build end-to-end machine learning solutions, from model development to user-facing interfaces.

This role is on-site.

Responsibilities

• Design, implement, and optimize models for regression, time-series forecasting, and deep learning.
• Lead the integration of LLMs and foundation models using LoRA and PEFT, managing performance and cost trade-offs.
• Drive Databricks adoption and automate model lifecycles using Docker and serverless functions for scalable endpoints.
• Build user-facing AI interfaces using Streamlit and standard front-end technologies (HTML/CSS/JavaScript).
• Apply systems thinking to ensure data quality, infrastructure stability, and downstream integration.

Required Skills

• 5+ years of professional experience in ML/AI engineering.
• Mastery of Python and its data ecosystem (pandas, numpy, scikit-learn).
• Expertise with PyTorch for deep learning model implementation.
• Hands-on experience with cloud platforms, specifically Azure or AWS.
• Proficiency in containerization using Docker.
• Deep technical knowledge of Databricks, including AutoML capabilities.
• Experience with CI/CD principles and version control (Git).
• Solid background in modern code development practices.

Preferred Skills

• Experience with LLM fine-tuning and prompt engineering.
• Familiarity with front-end stack (HTML/CSS/JavaScript).

Key Skills

Education

Any Gradute