Position Title	Sr. D&T Machine Learning Engineer	Function/Group	Digital and Technology
Location	Mumbai	Shift Timing	Regular
Role Reports to	Manager-MLE	Remote/Hybrid/in-Office	Hybrid

ABOUT GENERAL MILLS

We make foodthe 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

Function Overview

The Digital and Technology team at General Mills stands as the largest and foremost unit, dedicated to exploring the latest trends and innovations in technology while leading the adoption of cutting-edge technologies across the organization. Collaborating closely with global business teams, the focus is on understanding business models and identifying opportunities to leverage technology for increased efficiency and disruption. The team's expertise spans a wide range of areas, including AI/ML, Data Science, IoT, NLP, Cloud, Infrastructure, RPA and Automation, Digital Transformation, Cyber Security, Blockchain, SAP S4 HANA and Enterprise Architecture. The MillsWorks initiative embodies an agile@scale delivery model, where business and technology teams operate cohesively in pods with a unified mission to deliver value for the company. Employees working on significant technology projects are recognized as Digital Transformation change agents.

The team places a strong emphasis on service partnerships and employee engagement with a commitment to advancing equity and supporting communities. In fostering an inclusive culture, the team values individuals passionate about learning and growing with technology, exemplified by the Work with Heart philosophy, emphasizing results over facetime. Those intrigued by the prospect of contributing to the digital transformation journey of a Fortune 500 company are encouraged to explore more details about the function through the provided

Purpose of the role

General Mills, Digital and Technology India, is seeking Sr Machine Learning Engineer to join the Enterprise Data Capabilities Organization. This team builds enterprise level scalable and sustainable data and model pipelines to serve the analytic needs of business impacting problem statements. In this role, you are a critical member of the data science team focused to operationalize the ML and AI models, entails model management and monitoring too. The success is to recommend innovative ways to automate the MLOps pipelines on GCP and set standards that would ensure repeated success.

This capability is leveraged to fuel advanced Analytical solutions, Machine Learning and Deep Learning. It is also responsible for implementing and enhancing community of practice to determine the best practices, standards, and MLOps frameworks to efficiently delivery enterprise data solutions at General Mills.

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

KEY ACCOUNTABILITIES

Establish and Implement MLOps practices:

Development of end-to-end MLOps framework and Machine Learning Pipeline using GCP, Vertex AI and Software tools
Management of data pipelines including config, ingestion and transformation from multiple data source like Big Query, Dbt & Google cloud storage etc
Meta Data and statistics Data pipeline setup using GCP Bucket and MLMD
Re-Training and Monitoring Pipeline setup with multiple criteria Vertex AI
Serving Pipeline with multiple creation Vertex AI and GCP services
Resource and Infra Monitoring configuration and pipeline development using GCP
Automated pipeline Development for Continuous Integration (CI)/Continuous Deployment (CD) Continuous Monitoring (CM)/Continuous Training (CT) using GCP-native tool
Branching strategies and Version Control using GitHub
ML Pipeline orchestration and configuration using
DAG and Workflow orchestration using airflow/cloud
Code refactorization & coding best practices implementation as per industry standard
Technology-Stack suggestion based on 360 Deg
Implementing MLOps practices on project and follow the set MLOps
Support the ML models throughout the E2E MLOps lifecycle from development to maintenance

Architecture:

Micro Services Architecture and framework Development concept
Agile software Development concept
Architecture Design for HLD, LLD and Solution design

Team Mentoring:

Programming language Pattern Design implementation
Review projects PR and PBIs and suggestion for improvement
Knowledge sharing session with team for specific ML Ops
Guide/Mentor team members for MLOps framework development

Research, Evolve and Publish best practices:

Research and operationalize technology and processes necessary to scale ML Ops
Ability to research and recommend MLOps best practices on new technologies, platforms, and
MLOps pipeline improvement plan and suggestion

Communication and Collaboration:

Collaborate with technical teams like Data Science Lead, Data Scientist, Data Engineer and Platform
Knowledge sharing with the broader analytics team and stakeholders is
Communicate on the on-goings to embrace the remote and cross geography
Align on the key priorities and focus
Ability to communicate the accomplishments, failures, and risks in timely manner.

Embrace learning mindset:

Continually invest in your own knowledge and skillset through formal training, reading, and attending conferences and meetup

Documentation:

Document MLOps Process, Development, Architecture & Innovation etc and be instrumental in reviewing the same for other team members

MINIMUM QUALIFICATIONS

Total experience required 10-12 yrs
Min qualification - Bachelor's degree (full time)
Expertise and at least 5yrs of professional experience in MLOps E2E framework
Expertise in Data Transformation and Manipulation through Big-Query/SQL
Professional experience Vertex AI and GCP Services
Expertise in one of the programming Language Python/R
Airflow/Cloud composer Experience
Kubernetes/Kubeflow Experience
MLflow Professional experience
TFX Professional experience
Docker -container Experience
At least 5yrs of professional experience in the related field of Data Science
Strong communication skills both verbal and written including the ability to interacteffectively with colleagues of varying technical and non-technical
Passionate about agile software processes, data-driven development, reliability, and systematic

Expert level

. ML Ops E2E framework

. Big Query/SQL

. Python / R

. Vertex AI and GCP Services

. Docker-Container

. Kubeflow/Kubernetes

. TFX

. ~~Airflow~~

. MLflow

. GitHub

. Strong communication skills

Intermediate level

. Machine Learning and Deep Learning algorithms

. Agile techniques

. Demonstrates teamworking skills.

. Mentor others and lead best practices.

. Micro Services concept

. Power BI, Tableau, Looker

Basic Level

. Good to have domain knowledge: Consumer Packed Goods industry and data sources

. Analytic toolset- dbt, atscale, neo4j, Atlassian

PREFERRED QUALIFICATIONS

GCP certification
Understanding of CPG industry
Bcsic understanding of dbt
AutoML Concept
Machine Learning -Concept of Algorithms
Deep Learning- Concept of Algorithms
Time Series Analysis- Concept of Algorithms

Sr. D&T Machine Learning Engineer