Description

You design and deploy generative AI and machine learning solutions on Google Cloud Platform, owning the full lifecycle from data analysis to production MLOps.

This role is remote.

Responsibilities

• Architect and implement Retrieval-Augmented Generation (RAG) systems and fine-tune LLMs like Gemini for information extraction and summarization.
• Design, train, and deploy end-to-end ML models (classification, regression, forecasting) using Vertex AI and BigQuery.
• Build automated MLOps pipelines for data preprocessing, feature engineering, validation, and deployment.
• Partner with data scientists and engineers to define technical requirements and integrate AI solutions into business workflows.
• Mentor engineers on best practices for software engineering, MLOps, and scalable system design.

Required Skills

• 5+ years of professional experience building and deploying machine learning models in production.
• Advanced proficiency in Python and core libraries including PyTorch, scikit-learn, and Pandas.
• Hands-on experience with Google Cloud Platform, specifically Vertex AI, BigQuery, and GKE.
• Proven experience with RAG architectures, prompt engineering, and LLM fine-tuning.
• Strong SQL skills for complex data manipulation, aggregation, and analysis.
• Solid understanding of MLOps principles and CI/CD implementation.
• Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.

Preferred Skills

• Master’s or PhD in a relevant field.
• Experience building RAG systems from the ground up.
• Proven ability to lead technical projects and mentor teams.

Key Skills

Education

Bachelor's degree