About us AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa. About AB InBev Growth Group Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world. In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. As a Data Product Manager | Machine Learning Platform, you will own the product direction for a critical set of platform capabilities supporting the end-to-end machine learning lifecycle, from data and feature readiness through model development, deployment, and observability. You will work closely with data scientists, machine learning engineers, data engineers, and platform teams, driving the evolution of a platform that enables safe, scalable, and consistent delivery of machine learning solutions. What you'll do: - Define and Advance ML Platform Strategy - Set the vision and roadmap for your platform domain, prioritizing self-service, reliability, and reusability across the ML lifecycle. - Define and evolve standards, contracts, and shared tooling that enable scalable adoption of platform capabilities. - Drive Adoption and Platform Delivery - Partner closely with data science, ML engineering, and data engineering teams to identify workflow bottlenecks and platform gaps. - Deliver capabilities such as templates, CLIs, and standardized workflows, enabling users to execute repeatable tasks independently within clear guardrails. - Advance key platform capabilities, including: Feature governance; Training-serving parity; Model release and promotion standards; Deployment patterns (batch and real-time); Observability and monitoring. - Enable Scalable Machine Learning Operations - Improve and standardize how models move from development to production, reducing manual effort and increasing reliability. - Ensure platform capabilities provide clear ownership, consistent practices, and strong operational visibility. - Drive adoption of shared platform components across multiple data science teams and markets. What you'll need: - Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics, or a related technical field — or equivalent practical experience - Relevant years of professional experience with a strong technical foundation - Hands-on experience as a data scientist, machine learning engineer, or software engineer is strongly preferred - Experience working on complex, cross-functional technical problems involving data and platform systems - Fluency in English (required) - Portuguese or Spanish is a plus - Strong written and verbal communication skills - Comfortable discussing technical architecture, workflows, and trade-offs in depth; - Advanced communication skills in English (written and spoken); - Python (required): ability to read, understand, and reason about pipeline and platform code; discuss implementation trade-offs with engineers - SQL (required): ability to run independent investigations to validate data, features, and metrics; - Strong fluency in Machine Learning lifecycle and MLOps topics (e.g. Model training, evaluation, and experimentation; Monitoring, drift detection, and production operations; CI/CD for ML workflows; etc) Nice to Have: - Experience with Databricks and Azure. - Prior product management experience on developer, data, or ML platform products. - Familiarity with product and project management tools (Jira, Confluence). - Experience defining and prioritizing a roadmap, backlog, or release plan. - Comfort writing clear requirements, user stories, or acceptance criteria that engineering teams can execute against. More about you: - You´re passionate about software development and knows how to ensure its quality; - You´re motivated by building up world class solutions that impacts millions of users all over the world; - Experienced working in an environment which uses and stimulates DevOps culture; - You´re creative when solving problems and is continuously seeking improvements for processes and solutions; - You can communicate clearly with your team and the company to identify issues and demands; - You have the autonomy to recognize the current and new priorities, evaluating the impact of their outcomes in the final result. What We Offer: - Performance based bonus* - Attendance Bonus* - Private pension plan - Meal Allowance - Casual office and dress code - Days off* - Health, dental, and life insurance - Medicines discounts - WellHub partnership - Childcare subsidies - Discounts on Ambev products* - Clube Ben partnership - Scholarship* - School materials assurance - Language and training platforms - Transport allowance *Rules applied Equal Opportunity & Affirmative Action: AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. The following fields are optional, but anticipate the information for your registration*. Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. For more information: www.abinbev.com

Data Product Manager | Machine Learning Platform

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