Description

You will design, develop, and deploy machine learning models and generative AI solutions in a production environment. This role is remote.

Responsibilities

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

Required Skills

• 3+ years of professional experience building and deploying machine learning models in production.
• Advanced proficiency in Python and core libraries such as PyTorch, scikit-learn, and Pandas.
• Advanced proficiency in SQL for complex data manipulation and analysis.
• Hands-on experience with prompt engineering and fine-tuning Large Language Models.
• Experience with Google Cloud Platform or other major cloud providers.
• Solid understanding of MLOps principles and CI/CD.
• Practical experience with Vertex AI and BigQuery.

Preferred Skills

• Master’s or PhD in Computer Science, Data Science, Statistics, or a related quantitative field.
• Experience building RAG systems from the ground up.
• Specific experience with Google Cloud Storage and GKE.

Key Skills

Education

Master’s or PhD