Lead D&t Machine Learning Engineer Only 24h Left

Position TitleLead D T Machine Learning EngineerFunction GroupDigital and TechnologyLocationMumbai IndiaShift TimingRegularRole Reports toSr Manager- Data ScienceRemote Hybrid in-OfficeHybridABOUT GENERAL MILLSWe 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 xc3 xa4agen-Dazs weve 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 accelerateus 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 outGeneral 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 outWe advocate for advancing equity and inclusion to create more equitable workplaces and a better tomorrow JOB OVERVIEWFunction OverviewThe 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 providedPurpose of the roleGeneral 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 KEY ACCOUNTABILITIESEstablish and Implement MLOps practices Development of end-to-end MLOps framework and Machine Learning Pipeline using GCP Vertex AI and Software tools ML Serving Pipeline creation leveraging Vertex AI and GCP services Improve ML pipeline documentation and understandability Automate logging of model usage and predictions provided Improve general logging and diagnostic processes for easy identification and remediation of runtime issues in Data ML pipelines Automate monitoring of models both for failures and degradation over time 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 based triggers 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 Cloud Composer in GCP Kubeflow or similar orchestrators 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 support the post-production model runs to ensure any model performance degrades are proactively identified and 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 or pipelines 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 Suggest ongoing improvements in MLOps pipelines - plan and implementation Communication and Collaboration Design overall awareness sessions with the broader Global Data Science team and wider body of stakeholders Communicate on the on-goings to embrace team members working across different locations and culture Ability to communicate the accomplishments failures and risks in timely manner Knowledge sharing session with teams 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 ones knowledge and skillset through formal training reading and attending conferences and meetups MINIMUM QUALIFICATIONS Full time graduate from an accredited University 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 GitHub Actions 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 Good to have expertise in Data Transformation and Manipulation through GCP BigQuery SQL Professional experience with Vertex AI and GCP Services Strong proficiency in Python PREFERRED QUALIFICATIONS GCP Machine Learning certification Understanding of the Consumer-Packaged Goods CPG industry Exposure to Deep Learning Reinforcement Learning Large Language Models Prior experience with CPG industry Publications or contributions to the data science and AI community Certifications in AI machine learning or related fields