Intermediate Machine Learning Engineer - Bees Data
On-siteCampinas, São Paulo, Brazil
Job Summary
Implement and extend ML platform capabilities for training, inference, and batch serving while developing components of the model development workflow to improve consistency and reuse. Build and operate observability for models in training and production by monitoring, logging, and alerting for performance, quality, and drift in collaboration with platform and SRE partners. Support optimized model deployments for scaling, resource allocation, and inference tuning to meet cost, quality, and SLA targets. Troubleshoot pipeline and serving issues, document solutions, and share learnings with the team. This role sits within the Growth Group, which unifies B2B, DTC, Sales, and Marketing teams to drive digital transformation and organic growth for AB InBev through products like BEES and Ze Delivery.
Required Qualifications
- Bachelor's degree in computer science, engineering, mathematics, or another quantitative field
- Practical experience with ML platform components (e.g., feature pipelines, model registries, training and inference workflows)
- Solid software engineering fundamentals: clean code, testing, CI/CD, and maintainable system design
- Python
- PySpark
- SQL
- Exposure to Java
- Experience with Kubernetes
- Experience with Databricks
- Experience with Terraform
- Experience with Azure DevOps (Git)
- Experience with Azure Cloud
- Experience with ML frameworks/libraries such as Scikit-learn, PyTorch, TensorFlow, ONNX, and serving tools (BentoML, Kedro, Seldon, KServe, Triton Inference Server, etc.)
- Comfort collaborating across teams, communicating technical tradeoffs clearly, and learning from senior engineers on architecture and platform decisions
Desired Qualifications
- Exposure to Java is a plus
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