Senior Machine Learning Engineer - Bees Data
External
Abinbev · Campinas, BrazilPrepare for this interview
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About the role
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. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities.
Responsibilities
- Drive BEES AI's mission, vision, and ML strategy into concrete technical roadmaps and align architecture and standards with long-term goals.
- Own technical end-to-end delivery of ML pipelines-from architecture and data/feature pipelines through model development, deployment, and production scaling-in partnership with data, platform, and product teams.
- Design and standardize the ML model development framework (project structure, experimentation, versioning, reproducibility) to improve consistency and reuse across teams.
- Build and implement observability across the model lifecycle (training and production) via monitoring, logging, and alerting for performance, quality, and drift.
- Ensure optimized deployments that minimize cost and maximize quality (e.g., scaling, resource allocation, inference optimization) while meeting SLAs.
Requirements
- Bachelor's degree in computer science, engineering, mathematics, or any quantitative field. A master's degree is a plus.
- Relevant experience with ML platform architecture (e.g., feature stores, model registries, training and inference pipelines).
- Systems thinking (scalability, reliability, latency, cost)
- Software design patterns for building maintainable, production-ready ML systems.
- Python, PySpark, and SQL. Java, Rust, and NodeJS are a plus
- Kubernetes, Databricks, Terraform, Azure Devops (Git), Azure Cloud, ML Frameworks (BentoML, Kedro, Seldon, KServe, Triton Inference Server, etc.) and ML Libraries (Scikit Learn, Pytorch, Tensor Flow, ONNX, etc.)
- More about you:
- You´re motivated by building up world-class solutions that impact millions of users all over the world;
- 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.
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