Sr. D&T Machine Learning Engineer

India is am ong the top ten priority markets for General Mills, and hosts our Global Shared Services Centre. This is the Global Shared Services arm of General Mills Inc., which supports its operations worldwide. With over 1,300 employees in Mumbai, the center has capabilities in the areas of Supply Chain, Finance, HR, Digital and Technology, Sales Capabilities, Consumer Insights, ITQ (R&D & Quality), and Enterprise Business Services. Learning and capacity-building is a key ingredient of our success.

ABOUT GENERAL MILLS

We make foodthe world loves: 100 brands. In 100 countries. Across six continents.

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.

Analytical solutions, Machine Learning and Deep Learning

Data Scientists, Data Engineers, Platform Engineers and Tech Expertise

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 framewo rk
• 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