Lead D&T Machine Learning Engineer

Position Title

Lead ML Engineer

Function / Group

Digital and Technology

Location

Mumbai

Shift Timing

Regular

Role Reports to

Sr Manager- Data Science

Remote / Hybrid / in-Office

Remote / Hybrid

ABOUT GENERAL MILLS

We make food the world loves : 100 brands. In 100 countries. Across six continents. With iconic brands like Cheerios, Pillsbury, Betty Crocker, Nature Valley, and Häagen-Dazs, we’ve been serving up food the world loves for 155 years (and counting). Each of our brands has a unique story to tell.

How we make our food is as important as the food we make. Our values are baked into our legacy and continue to accelerate

us into the future as an innovative force for good. General Mills was founded in 1866 when Cadwallader Washburn boldly bought the largest flour mill west of the Mississippi. That pioneering spirit lives on today through our leadership team who upholds a vision of relentless innovation while being a force for good. For more details check out

General Mills India Center (GIC) is our global capability center in Mumbai that works as an extension of our global organization delivering business value, service excellence and growth, while standing for good for our planet and people.

With our team of 1800+ professionals, we deliver superior value across the areas of Supply chain (SC) , Digital & Technology (D&T) Innovation, Technology & Quality (ITQ), Consumer and Market Intelligence (CMI), Sales Strategy & Intelligence (SSI) , Global Shared Services (GSS) , Finance Shared Services (FSS) and Human Resources Shared Services (HRSS).For more details check out

We advocate for advancing equity and inclusion to create more equitable workplaces and a better tomorrow.

JOB OVERVIEW

General Mills, Digital and Technology India, is seeking a Lead ML Engineer to join our dynamic and innovative Global Data Science team. In this role, you are a critical member of the data science group focused on leading efforts in migrating ML-based solutions from concept to production-level operational excellence. You will lead initiatives building scalable, resilient, and automated solutions in GCP (Google Cloud Platform) to ensure that models deliver on organizational objectives. You will professionally engineer solutions considering notions of risk and FMEA (failure modes and effects analysis). The ideal candidate will have expertise in AI platforms, ML model development life cycle, model management including orchestration, deployment, and monitoring, GCP Vertex AI, and a proven track record of successful AI solution delivery.

The ML Engineering capability is leveraged to fuel advanced AI / ML solutions driving decision-making for critical enterprise needs. It is also responsible for implementing and enhancing the community of practice to determine the best practices, standards, and MLOps frameworks to efficiently deliver enterprise data solutions at General Mills.

This role works in close collaboration with Data Scientists, Data Engineers, Architects and other teams to support the analytic consumption needs. Enhances the performance of the models and automates the production pipelines to gain efficiency.

Roles & Responsibilities

Establish and Implement MLOps practices :

• Development of end-to-end MLOps framework and Machine Learning Pipeline using GCP, Vertex AI, and Software tools
• Serving Pipeline with multiple creation Vertex AI and GCP services. Improve ML pipeline documentation and understandability.
• Automate logging of model usage and predictions provided. Improve logging and diagnostic processes
• Automate monitoring of models both for failures and degradation. Automate monitoring of data sources to identify issues and / or data changes.
• Design and implement dynamic re-training of ML pipelines using event-based or custom logic
• Resource and Infra Monitoring configuration and pipeline development using GCP service.
• Branching strategies and Version Control using GitHub
• ML Pipeline orchestration and configuration using Airflow / Kubeflow.
• Code refactorization & coding best practices implementation as per industry standard
• Implementing MLOps practices on a project and establishing MLOps best practices.
• Lead the investigation and resolution of production issues, perform root cause analysis, and recommend changes to reduce / eliminate re-occurrence of issues.
• Optimize deployment and change control processes for models.
• Create and operationalize quality assurance processes for ML models

Lead the execution of ML Solutions @Scale :

Research, Evolve and Publish best practices :

Communication and Collaboration :

Embrace a learning mindset :

Good to have skills

Technical Skill proficiency expectations

Expert Level

Intermediate Level

Basic Level

Kubeflow / Airflow