Sr. Manager, AI/ML Platform Lead [T500-26942]

About McDonald’s:

One of the world’s largest employers with locations in more than 100 countries, McDonald’s Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonald’s global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.

Job Description:

We are excited to announce an opening for Sr. Manager, AI/ML Platform Lead at MCC India.

Please find below the details of the role and its responsibilities.

Skills Required:

• Python, GCP, Vertex AI, Docker, Kubernetes, Machine Learning, Artificial Intelligence,
• MLOps, AIOps

Experience Range:

11 - 15 years.

Job Title: AI / ML Platform Lead.

Experience Level Senior / Lead (11-15 years).

About the Role:

We are seeking an experienced and innovative AI & ML Platform Lead who will own and evolve AI/ML platform strategy and execution to accelerate model development, deployment, and operations are scale. The role will act as Technical Subject Matter Expert (SME) across the organization, shaping platform standards, architecture, governance and roadmap while partnering with product, engineering, security, and data teams to deliver a reliable, secure and cost-efficient AI/ML platform.

Key Responsibilities:

AI / ML Platform Strategy & Vision:

• Serves as the Technical SME for the AI / ML platform.
• Define and drive the AI/ML platform vision, reference architecture, and roadmap aligned to enterprise strategy.
• Own the platform capability model covering experimentation, training, feature management, model lifecycle and deployment enablement.
• Evaluating emerging AI/ML technologies and determining platform-fit and standardization strategy.

Standardized platform components including:

Developer Enablement & Golden Paths

Governance & Compliance:

• Model onboarding and training frameworks.
• Feature engineering and feature lifecycle abstractions.
• Model packaging, versioning and promotion constructs.
• Inference enablement patterns as reusable platform services.
• Build self-service platform capabilities that abstract infrastructure and complexity from practitioners.
• Define and publish golden paths, templates, SDK’s and API’s for common workflows.
• Drive adoption through documentation, reference implementations, and onboarding guides.
• Act as a trusted advisor on platform usage and best practices.

Embed governance-by-design into the platform:

Cross-Functional Collaboration:

• Model metadata, lineage approvals, and auditability
• Standardized interfaces for risk, compliance and responsible AI checks
• Define platform hooks for bias detection, explain ability, and policy enforcement.

Partner with: People Leadership & Technical Culture

Work location: Hyderabad, India.

• Data and AI / ML engineering team on Data and Feature abstractions
• Security, Risk and Architecture on guardrails and enterprise standards
• Lead and mentor AI/ML platform engineers with a strong engineering-first mindset.
• Establish platform engineering best practices, coding standards, and design review processes.
• Foster culture of reusability, automation, and long-term platform thinking.
• 11+ years of overall experience with 5+ years in designing AI/ML platforms on cloud platforms, preferably GCP.
• Strong expertise in Google Cloud Platform (GCP), including Vertex AI, Big Query, Dataflow, Cloud Storage, Cloud Functions, Cloud Run, AI Platform Pipelines, and related services.
• 5+ years of proven hands-on experience designing, building, and evolving core AI/ML platform components such as: Model onboarding, feature engineering, model packaging, versioning deployment enablement patterns, feature lifecycle abstractions.
• 5+ years of experience of code management and reliability using GitHub, pytest, and SonarQube.
• Proficiency in Python and Infrastructure – as – code (Terraform or equivalent).
• Experience with workflow orchestration tools (Astronomer, Airflow, or similar).
• Knowledge of containerization (Docker, Kubernetes) and serverless architecture.
• Able to read, review, and guide production-quality code, and to prototype or build reference implementations when needed.
• Excellent communication skills and ability to translate…