Job Description

Shift Timings: 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 H agen-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 MillsWorks 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: Lead D&T Machine Learning Engineer Location: Mumbai 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. 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 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 : Partners with business stakeholders to design the right deliver value-added insights and intelligent solutions through ML and AI. Collaborates with Data Science Leads, ML System Engineering and Platform teams to ensure the models are deployed in a scaled and optimized way. Additionally, ensure support the post-production to ensure model performance degrades are proactively managed. Play a lead role in spearheading the development effort of new standards (design patterns, coding practices, orchestration patterns) and drive value and adoption across the Data Science team Is considered an expert in the ML Ops and Model management space; brings together business knowledge, architecture, resources, people, and technology to create more effective solutions Research, Evolve and Publish best practices: Research and operationalize technology and processes necessary to scale ML Ops Recommend model changes to optimize cloud spend. Ability to research and recommend MLOps best practices on new technologies, platforms, and services. Drive ideation, design, and creation of new ML Architecture patterns in discussion with the Enterprise Architecture team. MLOps pipeline improvement plan and suggestion Communication and Collaboration: Knowledge sharing with the broader analytics team and stakeholders. Communicate on the on-goings to embrace the remote and geographical culture. Ability to communicate the accomplishments, failures, and risks in timely manner. Knowledge sharing session with team for specific ML Ops topics. Coach and Mentor junior ML members in the team. Foster a collaborative and innovative team environment. Contribute to the overall effort to educate stakeholders on AI practices. Closely collaborates with the stakeholders on projects and data science leaders to ensure practices are developed and enhanced to support accelerated analytic development and maintainability. Embrace a learning mindset: Continually invest in one\'s knowledge and skillset through formal training, reading, and attending conferences and meetups Must - have technical skills and experience Advanced degree in a quantitative field (CS, engineering, statistics, math, data science). Proven technical leadership in a large, complex matrixed organization. Relevant Machine Learning experience of 6+ years and overall 12+ years of Industry experience. Experience in supervised ML algorithms, optimization, and performance tuning. Track record of producing machine learning models and production infrastructure at scale. Strong verbal and written communication skills 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. Passion for learning new technologies and solving challenging problems. Good understanding of CI, CD, TDD, and tools such as Jenkins. Strong understanding of orchestration frameworks such Airflow/Kubeflow/MLFlow. Agile software development experience such as Kanban and Scrum. Experience in software version control team practices and tools such as GIT and TFS. Expertise in Data Transformation and Manipulation through Big-Query/SQL Professional experience with Vertex AI and GCP Services. Strong proficiency in Python. Good to have skills GCP Machine Learning certification Understanding of CPG industry Exposure to Deep Learning/RL/LLMs Prior experience with CPG industry. Publications or contributions to the data science and AI community. Certifications in AI, machine learning, or related fields. Technical Skill proficiency expectations Expert level Intermediate Level Basic Level ML Ops framework Big Query/SQL Python / R Vertex AI and GCP Services Docker-Container ML Orchestrator Kubeflow/Airflow GitHub Strong communication skills Machine Learning and Deep Learning algorithms Agile techniques Demonstrates teamwork skills. Mentor others and lead best practices. Understanding of ML Architecture Consumer Packaged Goods domain knowledge Large Language Models and deployment architecture Graph database Tools like Neptune.AI/ML Flow Feature Store (GCP Vertex Feature Store, Feast etc)

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