Description

Lead the design and implementation of advanced AI and ML solutions in production.

This role is remote.

Responsibilities

• Design, develop, and fine-tune Generative AI solutions using models like Gemini for information extraction and summarization.
• Architect and implement Retrieval-Augmented Generation (RAG) systems to ensure context-aware responses.
• Design and deploy ML models (classification, regression, forecasting) on Google Cloud Platform.
• Build and maintain automated MLOps pipelines for data preprocessing, training, and deployment using Vertex AI and BigQuery.
• Partner with stakeholders to define requirements and champion ML/software engineering best practices.

Required Skills

• 5+ years of professional experience building and deploying ML models in production.
• Advanced proficiency in Python and its core data science/ML libraries (PyTorch, scikit-learn, Pandas).
• Advanced proficiency in SQL for complex data manipulation.
• Hands-on experience in prompt engineering or fine-tuning Large Language Models (e.g., Gemini).
• Hands-on experience with Google Cloud Platform (GCP).
• Solid understanding of MLOps principles and experience with tools like Vertex AI.
• Experience with GCP services including BigQuery, Google Cloud Storage, and GKE.
• Experience building RAG systems from the ground up.

Preferred Skills

• Master’s or PhD in a relevant quantitative field.
• Proven ability to lead technical projects and mentor other engineers.

Key Skills

Education

Master’s or PhD