Job Offers
Description
Job Description
Are you ready to work as a Machine Learning Engineer for our Global business in Vitoria? You will be part of a growing team to create and support global digital developments for PepsiCo around topics related with Revenue Management, Supply Chain, Manufacturing, Logistics.
You will be part of a collaborative interdisciplinary team around data, where you will be responsible of building deployable statistical/machine learning models, starting from the discovery phase. You will work with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments.
You will be an internal ambassador of the team's culture around data and analytics. You will provide stewardship to colleagues in the areas that you are an specialist or you are specializing.
Your Day to Day with us:
- Partner with data scientist working on discovery, prototypes and pilot. Focus on experiment tracking.
- Work with data engineers regarding data pipelines and data versioning.
- Adopt the best MLOps standards to design and develop scalable end-to-end machine learning pipelines.
- Build and deploy machine learning models that run in cloud pipelines.
- Help drive optimization, testing, and tooling to improve quality (unit tests).
- Monitor model performance.
- Support large-scale experimentation done by data scientists.
- Create documentation for insights and knowledge transfer.
- Create and audit reusable packages or libraries.
Qualifications/Requirements
What experience do you need to succeed?
- Experience with MLOps framework design and building machine learning pipelines.
- Familiarity using cloud platforms (e.g. Azure, AWS or GCP) to serve machine learning models in production.
- Knowledge of code development best practices and tooling (e.g. version control, test-driven development, CI/CD)
- ETL and/or data wrangling techniques.
- Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.
- Proficiency in Python development.
- Knowledge of containerization technology (Docker/Kubernetes) and REST API design.
- Business storytelling and communicating data insights in business consumable format.
- Agile methodology for team work and analytics 'product' creation.
What makes us different?
- Hybrid work model: combination of remote and office options
- Flexible work schedules & Work-life balance
- Position with growth possibilities
- Develop a Machine Learning career in an international company
- Create your leadership footprint as you grow
- Be part of a dynamic collaborative culture