AI GCP Architect

Virtusa • Fremont, CA

1h

About The Position

We urgently need someone with strong hands-on experience in Google CCAI and Vertex AI, along with deep expertise in Speech-to-Text and intent classifications.
Advanced experience in production grade Machine Learning Model design and implementation including LLMs, Model Evaluation and MLOps.
In depth exposure and experience in designing and implement machine learning models using Google Vertex AI & Python in the context of Conversational AI.
Collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient AI solutions.
Design, build, and deploy machine learning models on the Google Cloud Platform. Experience in using Google CCAI/GoogleInsights CES platform and it’s components.
Experience in agentic architecture based implementations and advanced Retrieval Augmented Generation.
Conduct thorough testing and validation to ensure the accuracy and reliability of the models. Experience in Eval frameworks and eval metrics.
Optimize and fine-tune machine learning models for performance and efficiency and accuracy. Experience in Parameter Efficient Fine Tuning will be an added advantage.
Stay updated on the latest advancements in machine learning and AI technologies.
Over all 10+ years of Experience required.

Requirements

• Strong hands-on experience in Google CCAI and Vertex AI
• Deep expertise in Speech-to-Text and intent classifications
• Advanced experience in production grade Machine Learning Model design and implementation including LLMs, Model Evaluation and MLOps.
• In depth exposure and experience in designing and implement machine learning models using Google Vertex AI & Python in the context of Conversational AI.
• Experience in using Google CCAI/GoogleInsights CES platform and it’s components.
• Experience in agentic architecture based implementations and advanced Retrieval Augmented Generation.
• Experience in Eval frameworks and eval metrics.
• 10+ years of Experience

Nice To Haves

• Experience in Parameter Efficient Fine Tuning

Responsibilities

• Collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient AI solutions.
• Design, build, and deploy machine learning models on the Google Cloud Platform.
• Conduct thorough testing and validation to ensure the accuracy and reliability of the models.
• Optimize and fine-tune machine learning models for performance and efficiency and accuracy.
• Stay updated on the latest advancements in machine learning and AI technologies.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed