Senior Machine Learning Engineer

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?
AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev.

The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology.

The teams are transforming Operations through Tech and Analytics.
Do You Dream Big?
We Need You.
Job Description
Job Title: Senior ML Engineer
Location: Bangalore (Onsite)
Reporting to: Senior Manager, Analytics
PURPOSE OF ROLE
Anheuser-Busch InBev (AB InBev)’s Supply Analytics is responsible for building competitive differentiated solutions that enhance brewery efficiency through data-driven insights.

We optimize processes, reduce waste, and improve productivity by leveraging advanced analytics and AI-driven solutions.
As a Senior MLE, you will be responsible for driving the technical backbone of the internal ML platform—from model containerization and deployment at scale to architecting backend repos and pipelines that enable integration with the software/frontend layers.

You will lead the end-to-end ML engineering lifecycle for edge deployments, ensuring high availability, observability, and scalability of the platform across 100+ brewery deployments globally.
KEY TASKS AND ACCOUNTABILITIES
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
Lead the entire edge deployment lifecycle, from model training to deployment and monitoring on edge devices
Develop, and maintain a scalable Edge ML pipeline that enables real-time analytics at brewery sites
Optimize and containerize models using Portainer, Docker, and Azure Container Registry (ACR) to ensure efficient execution in constrained edge environments.
Own and manage the GitHub repository, ensuring structured, well-documented, and modularized code for seamless deployments
Establish robust CI/CD pipelines for continuous integration and deployment of models and services
Implement observability layers for data, feature, inference, and pipeline health (e.g., logging, monitoring, alerting), ensuring reliable and quick feedback loops
Ensure compliance with security and governance best practices for data and model deployment in edge environments
Collaborate with product and software teams to ensure backend architecture seamlessly integrates with frontend and operator-facing tools
Mentor other team members and set technical standards and review processes for high-quality, scalable, and secure code delivery
You will also develop internal tools/utils that improve productivity of entire team.
QUALIFICATIONS, EXPERIENCE, SKILLS
Education:
Academic degree in, but not limited to, Bachelors or master's in computer application, Computer science, or any engineering discipline.
Experience:
5+ years of experience developing scalable and high-quality ML models and backend ML engineering infrastructure.
Strong problem-solving skills with an owner’s mindset—proactively identifying and resolving bottlenecks
Technical/Functional Skills:
Mandatory Skills:
Python (pandas, NumPy, SciPy, scikit-learn, TensorFlow) - Expert
GitHub, Docker, CI/CD Pipelines – Expert
ML Model Design & Deployment– Expert
Model Deployment – Expert
Azure Cloud Architecture for ML– Advanced
Containerization & Edge Deployment (Portainer, Kubernetes, ACR) – Advanced
Observability (Logging, Monitoring, Alerting) – Intermediate
Databricks (Workflows, Cluster Creation, Repo Management) – Intermediate
Unit Testing – Intermediate
Preferred (Good to have) Skills:
DevSecOps & Automation – Intermediate
Computer Vision / Edge Vision Deployments – Beginner
Multi-repo or Monorepo ML Architecture – Intermediate
Real-time Analytics & Edge AI Deployments – Intermediate
Open-source ML Tooling Contributions – Beginner
Behavioral Skills:
You take full ownership of your projects & understand end-to-end expectations.
You demonstrate thought leadership at work, assert ideas & influence overall direction of solutions.
Collaborate with team members, share selflessly & improve the quality of code, models etc.
Ability to simplify communicating the output of your work for business, create compelling documentation or any artifacts that connects business to the solutions.
A drive to build platforms that power real business impact at scale
And above all of this, an undying love for beer!
We dream big to create future with more cheers .

Required Skill Profession

Computer Occupations