Generative AI Engineer (GCP)

TechDigital Group; Frisco (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

A technology solutions provider in Frisco is seeking a Python Technical Lead to design and develop machine learning models and Generative AI solutions. This role requires 5+ years of experience in a production environment, advanced Python and SQL skills, and a strong background in MLOps. Collaborate with stakeholders to frame problem statements and mentor other engineers. The position offers an opportunity to work with cutting-edge technologies in cloud and AI.

Qualifications

• 5+ years of experience in deploying machine learning models in production.
• Strong programming skills in Python and data science libraries.
• Advanced SQL skills for data manipulation and analysis.

Responsibilities

• Design and develop Generative AI solutions using models.
• Implement advanced Retrieval‑Augmented Generation (RAG) systems.
• Conduct deep data analysis to guide feature engineering.

Skills

Generative AI Development

End‑to‑End Machine Learning

Collaboration & Strategy

Advanced Python proficiency

Advanced SQL proficiency

MLOps experience

Education

Bachelor's degree in Computer Science or related field

Master's or PhD in a relevant field

Tools

Google Cloud Platform (GCP)

PyTorch

scikit‑learn

Vertex AI

BigQuery

Job description

Python Technical Lead - Data Analysis, SQL / Machine Learning Engineer (Generative AI & Cloud)

Responsibilities

• Generative AI Development: Design, develop, and fine‑tune Generative AI solutions using models like Google's Gemini for tasks such as information extraction, document summarization, and report generation.
• Architect and implement advanced Retrieval‑Augmented Generation (RAG) systems to enhance model accuracy and provide verifiable, context‑aware responses.
• Research and apply emerging GenAI techniques, such as agentic frameworks, to build more autonomous and capable systems.
• End‑to‑End Machine Learning: Design and deploy a wide range of ML models (classification, regression, forecasting, etc.) on Google Cloud Platform.
• Build and maintain robust, automated MLOps pipelines for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI, BigQuery, etc.
• Conduct deep data analysis to uncover insights, validate hypotheses, and guide feature engineering for improved model performance.
• Collaboration & Strategy: Partner closely with data scientists, software engineers, and other business stakeholders to frame problem statements, define technical requirements and deliver integrated AI/ML solutions.
• Champion best practices in software engineering and MLOps to ensure the quality, maintainability, and scalability of our machine learning systems.
• Continuously evaluate and stay current with the latest advancements in the ML and GenAI landscape.

Qualifications

• Experience: 5+ years of professional experience building and deploying machine learning models in a production environment.
• Education: Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Programming: Advanced proficiency in Python and its core data science/ML libraries (e.g., PyTorch, scikit‑learn, Pandas).
• Data & SQL: Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
• Generative AI: Demonstrable, hands‑on experience in prompt engineering and/or fine‑tuning Large Language Models (e.g., Gemini).
• Cloud Platform: Hands‑on experience with a major cloud provider, with a strong preference for Google Cloud Platform (GCP).
• MLOps: Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD).
• Master's or PhD in a relevant field.
• Specific experience with GCP services like Vertex AI, BigQuery, Google Cloud Storage, and GKE.
• Experience building RAG systems from the ground up.
• Proven ability to lead technical projects and mentor other engineers.