Description

You will design, develop, and deploy machine learning and generative AI solutions within a production environment.

Responsibilities

• Design and fine-tune generative AI solutions using models like Gemini for summarization, extraction, and report generation.
• Architect and implement Retrieval-Augmented Generation (RAG) systems and agentic frameworks to improve model autonomy and accuracy.
• Build and maintain automated MLOps pipelines for preprocessing, training, and deployment using Vertex AI and BigQuery.
• Deploy diverse ML models including classification, regression, and forecasting models on Google Cloud Platform.
• Collaborate with software engineers and data scientists to define technical requirements and deliver scalable AI/ML systems.

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.
• Advanced SQL skills for complex data manipulation, aggregation, and analysis.
• Hands-on experience with prompt engineering and fine-tuning Large Language Models.
• Experience with Google Cloud Platform (GCP) and MLOps tools like Vertex AI and CI/CD.
• 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.
• Hands-on experience with BigQuery, Google Cloud Storage, and GKE.
• Ability to lead technical projects and mentor other engineers.

Key Skills

Education

Any Graduate