AI Infrastructure Architect

Accenture PLC; Gurugram District; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Accenture PLC is seeking an AI Infrastructure Architect to design and build custom AI infrastructure and hardware solutions. You will optimize performance, power, cost, and scalability of the computational stack, and advise on technology selection and full stack integration.

The role involves collaborating with data scientists to deploy and operationalize models, maintaining ML pipelines, and ensuring reliability across training, evaluation, and deployment stages within a large enterprise

Qualifications

• Experience with Google Cloud Machine Learning Services is mandatory.
• Minimum of 5 years of professional experience in AI infrastructure.
• Fifteen years of full-time education is required.

Responsibilities

• Build and maintain ML pipelines for training, evaluation, and deployment
• Support model versioning, packaging, and CI/CD for ML workflows
• Monitor deployed models for performance, drift, and reliability
• Automate data preprocessing and feature pipelines
• Collaborate with data scientists to deploy and operationalize models
• Troubleshoot infrastructure and pipeline issues
• Maintain documentation of ML infrastructure and workflows

Skills

Google Cloud Machine Learning Services

Education

15 years full time education

Tools

Machine Learning Operations

Job description

Project Role

AI Infrastructure Architect

Project Role Description

Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration.

Must have skills

Google Cloud Machine Learning Services

Good to have skills

Machine Learning Operations

Minimum 5 year(s) of experience is required

Educational Qualification

15 years full time education

Summary

Build and maintain ML pipelines for training, evaluation, and deployment

Roles & Responsibilities

• Build and maintain ML pipelines for training, evaluation, and deployment
• Support model versioning, packaging, and CI/CD for ML workflows
• Monitor deployed models for performance, drift, and reliability
• Automate data preprocessing and feature pipelines
• Collaborate with data scientists to deploy and operationalize models
• Troubleshoot infrastructure and pipeline issues
• Maintain documentation of ML infrastructure and workflows

Professional & Technical Skills

• Support scaling of training/inference infrastructure 15 years full time education

Equal Employment Opportunity Statement

All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

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