.OverviewAre you ready to drive PepsiCo's digital evolution and accelerate transformation across our global operations?As ML Engineer within a DS department, you will be designing and implementing software to complement DS developments, providing an engineering point of view to their ML solutions. More specifically, you will be working very closely with DS enriching a structuring their solution by:Building components related CI/CD, monitoring, model explainability, data and model drifting, or ML lifecycle management.Enhancing the collaboration between DE and DS by defining Data Quality validation or linking Data and ML pipelines.Working with IT teams to define templates and/or processes to facilitate the developments and deployments of ML solutions.Contributing with DS teams as Software Engineer/Developer, boosting the reusability of their solution.You will be an internal ambassador of the team's culture around data and analytics. You will provide stewardship to colleagues in the solution development landscape and further lead the onboarding of new developments in AI within the PepsiCo domain leading the development of best practices and standard ways of working.ResponsibilitiesYour day to day with us:Develop and maintain scalable, modular and reusable software components, guidelines, and templates related to data and ML projects.Serve and support the integration and adoption of software components, guidelines, and templates in new and existing ML solutions.Identify and audit reusable components developed for specific projects.Design and implement the required enhancements to make project developments reusable in other projects.Definition of standard ways of working and best practices of software development.Enhance the cross-functional collaboration between Data Scientists, Data Engineers, Software Engineers, and IT.Contribute to the development of ML solutions to serve specific business requirements.Research in state-of-the-art tools and methodologies.Create documentation for learnings and knowledge transfer.QualificationsWhat you will need to succeed:2+ years working in a team delivering production level ML solutions.2+ years of experience in ETL and/or data wrangling techniques.2+ years of experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.Experienced with Python and SQL.Practiced in Git.Practiced in at least one cloud computing platform (Azure, AWS, Google Cloud). Azure preferred. Certification is a plus.Practiced in Databricks and/or Azure ML. Experience with Kubernetes is a plus.Practiced in Spark or other distributed data/ML frameworks.Familiar with MLflow.Familiar with Docker.Familiar with Object Oriented Programming.Familiar with Agile methodology.Additional qualifications that will make you stand out for this position:Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities
