Description

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 to improve scalability.
• Integrate data and model pipelines within production environments while diagnosing inconsistencies and documenting assumptions.
• Collaborate with data science teams to review feature documentation and ensure dataset accuracy.
• Perform data discovery and analysis of raw sources to meet model development needs.
• Write and maintain model monitoring scripts to diagnose issues and coordinate resolutions.

Required Skills

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

Preferred Skills

• Experience with API design and development.

Key Skills

Education

Any Graduate