Description

You will build and optimize scalable AI/ML solutions and complex data pipelines.

This role is hybrid.

Responsibilities

• Develop and optimize complex data pipelines using machine learning engineering principles.
• Integrate and optimize data and model pipelines within production environments.
• Collaborate with data science teams to review model-ready datasets and feature documentation.
• Perform data discovery and analysis on raw sources to meet model development requirements.
• Write and maintain model monitoring scripts to diagnose issues and coordinate resolutions.

Required Skills

• 5-8 years of relevant work experience.
• 3+ years of hands-on experience designing ETL pipelines using AWS Glue and SageMaker.
• Proficiency in Python, including PySpark and PySQL.
• Strong understanding of cloud technologies, specifically AWS and Azure.
• Experience with Large Language Models (LLMs), GenAI, RAG, Prompt Engineering, and Model Evaluation.
• Familiarity with Feature Store usage.
• Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
• Experience with exploratory data exploration and tracking data lineage.

Preferred Skills

• Experience with API design and development.

Key Skills

Education

Any Graduate