Position Title: Sr. Machine Learning Engineer Function/Group: Digital and Technology Country: India Location: Mumbai Role Reports to: Manager-MLE Geographical Scope of the Role Location: Global Percentage of travel required: 1% International Remote/Hybrid/inOffice Hybrid On-call required Yes Shift Regular 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. The awards and recognition we’ve received showcase our commitment to be a force for good: • • • • • • • • • • • • • • World’s Most Admired Companies, Fortune 2022 America’s Most Responsible Companies, Newsweek 2022 100 Best Corporate Citizens, 3BL 2021 Best Places to Work for LGBTQ Equality, Human Rights Campaign 2022 100 Best Companies, Seramount 2021 Diversity Best Practices Leading Inclusion Index, Seramount 2021 Best Companies for Dads, Seramount 2021 Best Companies for Multicultural Women, Seramount 2021 Top 10 Companies for Executive Women, Seramount 2021 Military Friendly Employer Bronze, VIQTORY 2021 Best Place to Work, Canada, Greater Toronto, 2021 Top 50 – India’s Best Workplaces for Women, 2021 Top Workplaces in Brazil, 2021 Asia’s Best Workplaces, 2021 Hungry for What’s Next We exist to make food the world loves, and it shows. Our passion for people, doing good and creating delicious food has energized us for over 150 years. Breaking away from the pack is how we win, so we need your unique perspectives: your quirks, ‘crazy’ ideas, rigor and insatiable curiosity to make it happen. We want people who constantly experiment, embracing the new and bold, who keep pushing to turn ideas into reality, no matter how big or small. We’ve learned becoming the undisputed leader in food means continuously reshaping, reimagining and rebuilding— that only happens when you surround yourself with those who are hungry for what’s next. For more details check out www.generalmills.com General Mills India Centre General Mills India Center (GIC) operates out of Mumbai and supports the global operations of General Mills. The center was established in 2005 and has grown in strength. Today, we are a vibrant and diverse team of over 1500 employees that come together to champion business services for the various global entities of General Mills in the areas of Business Operations, Analytics Consulting, Logistics, Finance, IT Development & Technology Consulting, Consumer & Market Intelligence, Sales Capabilities, Research & Development. Digital and Technology team Digital and Technology is the largest team in GIC, which focuses on understanding the latest and innovative trends in technology and leading the adoption of cutting-edge technologies at General Mills. The team closely collaborates with global business teams to understand business models and assess where technology can leveraged to bring efficiency and disruption. Be it AI/ML, Data Science, IoT, NLP, Cloud, Infrastructure, RPA and Automation, Digital Transformation, Cyber Security, Blockchain or Enterprise Architecture, GIC Digital and Technology has something for every technology enthusiast who wants to work here. Our Millworks initiative is where we bring agile@scale delivery model to life. Here, business and technology teams work cohesively in pods as ONE team, driven by a singular mission and focused on delivering value for the Company. Our employees, who work on large technology projects of strategic importance, are the Digital Transformation change agents. Our service partnerships and employee engagement are centred on advancing equity and strengthening communities. We believe in an inclusive culture and trust in the power of people who have a passion for learning and growing with technology. We believe in “Work with Heart”. Work with Heart is focused on results, not facetime. If you are passionate about the latest in technology and want to make an impact on the digital transformation journey of a Fortune 500 company, we're waiting for you. Job Overview Role: Sr ML Engr (Sr. Machine Learning Engineer) Location: Mumbai 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 Expertise to support the analytic consumption needs. Enhances the performance of the models and automates the production pipelines to gain efficiency. Role Responsibilities 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 service. • Automated pipeline Development for Continuous Integration (CI)/Continuous Deployment (CD) Continuous Monitoring (CM)/Continuous Training (CT) using GCP-native tool stack. • Branching strategies and Version Control using GitHub • ML Pipeline orchestration and configuration using Kubeflow. • DAG and Workflow orchestration using airflow/cloud composer. • Code refactorization & coding best practices implementation as per industry standard • Technology-Stack suggestion based on 360 Deg Analysis. • Implementing MLOps practices on project and follow the set MLOps practices. • 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 topics. • 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 services. • MLOps pipeline improvement plan and suggestion Communication and Collaboration: • Collaborate with technical teams like Data Science Lead, Data Scientist, Data Engineer and Platform owner. • Knowledge sharing with the broader analytics team and stakeholders is essential. • Communicate on the on-goings to embrace the remote and cross geography culture. • Align on the key priorities and focus areas. • 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. Must - have technical skills and experience • • • • • • • • • • • • • Minimum qualification- Bachelor’s degree (Full Time) Total Experience required 12-15 Years Expertise and at least 5 Years 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 interact effectively with colleagues of varying technical and non-technical abilities. • Passionate about agile software processes, data-driven development, reliability, and systematic experimentation. Good to have skills • • • • • • • GCP certification Understanding of CPG industry Basic understanding of dbt. AutoML Concept Machine Learning -Concept of Algorithms Deep Learning- Concept of Algorithms Time Series Analysis- Concept of Algorithms Skill proficiency expectations Expert level Intermediate Level Basic 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 • • • • • Machine Learning and Deep Learning algorithms Agile techniques Demonstrates teamworking skills. Mentor others and lead best practices. Micro Services concept Power BI, Tableau, Looker • Good to have domain knowledge: Consumer Packed Goods industry and data sources Analytic toolset- dbt, atscale, neo4j, Atlassian
