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Anheuser-Busch InBev · GCC Service India Pvt. Ltd.

Senior Machine Learning Engineer

GCC Service India Pvt. Ltd.Full-timeSenior individual contributorData & Analytics

Listed on Anheuser-Busch InBev’s official careers site. Posted September 23, 2026. Check that it is still open and apply there.

Apply on Anheuser-Busch InBev’s careers site →

Job description

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential.

The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? Ø Own the backend engineering strategy for the platform, ensuring repos, pipelines, and modular components are structured for scalable integration with software applications and visualization layers Ø Lead the entire deployment lifecycle, from model training to deployment and monitoring on devices Ø Develop, and maintain a scalable ML pipeline that enables real-time analytics for Test & Learn experimentation across business functions Ø Optimize and containerize models using Docker, and Azure Container Registry (ACR) etc. to ensure efficient execution in constrained environments.

PySpark deep understanding is a must. Ø Own and manage the GitHub repository, ensuring structured, well-documented, and modularized code for seamless deployments Ø Establish robust CI/CD pipelines for continuous integration and deployment of models and services Ø Implement observability layers for data, feature, inference, and pipeline health (e.g., logging, monitoring, alerting), ensuring reliable and quick feedback loops Ø Ensure compliance with security and governance best practices for data and model deployment in centralized data environments Ø Collaborate with product and software teams to ensure backend architecture seamlessly integrates with frontend

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