Anheuser-Busch InBev

2 weeks ago

Manager Machine Learning Platform - Bees Data

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Lead a team building and scaling BEES’s Machine Learning Platform, enabling ML, data, product, and engineering teams to develop, deploy, operate, and govern production ML systems with speed, reliability, and quality. Own the platform roadmap and execution across MLOps, model development, serving, infrastructure, reliability, observability, governance, and developer experience, driving reusable capabilities, engineering standards, SLO/SLA-driven operations, and adoption across BEES.

Location: Campinas

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Lead a team responsible for building and scaling BEES’s Machine Learning Platform for production ML systems.
•Translate ML strategy into a platform roadmap balancing business priorities, reliability, developer experience, cost efficiency, and long-term architecture.
•Own execution across MLOps, model development workflows, model serving, infrastructure, reliability, observability, governance, and developer experience.
•Drive end-to-end delivery of reusable platform capabilities (ML pipelines, experiment tracking, model registries, feature/data workflows, training infrastructure, inference services, monitoring, alerting, governance).
•Establish engineering standards and paved paths (CI/CD, testing, versioning, reproducibility, release management, rollback strategies, documentation, operational readiness) and drive SLO/SLA-based operational excellence.

Pay and Benefits

Perks:Annual BonusHealth InsuranceDentalLife InsurancePensionMeal AllowanceDays OffCommuter BenefitsChildcareLearning Budget

Key Requirements

•Bachelor’s degree in computer science, engineering, mathematics, or another quantitative field (or equivalent practical experience), with a master’s degree a plus.
•Experience managing or technically leading engineering teams building production ML/data/developer platforms, distributed systems, or cloud infrastructure.
•Strong understanding of the ML lifecycle, including data preparation, feature engineering, experimentation, training, evaluation, packaging, deployment, serving, monitoring, retraining, and governance.
•Ability to lead across multiple ML platform disciplines, including MLOps, model development workflows, model serving, infrastructure, reliability, observability, and platform governance.
•Technical credibility with modern ML platform and cloud-native technologies (e.g., Python, SQL, PySpark, Kubernetes, Databricks, Terraform, Azure DevOps/Git CI/CD, Azure Cloud).

Education:Bachelor's

Skills:LeadershipCommunicationStakeholder managementSystems thinkingStrategic prioritization

Languages:English

Tech Stack:PythonSQLPySparkKubernetesDatabricksTerraformAzure DevOpsGit-based CI/CDAzure CloudModel registriesFeature storesML pipelinesInference platformsPyTorchTensorFlowScikit-learnONNXBentoMLKedroSeldon

Company Brief

Anheuser-Busch InBev

A global brewer producing, distributing, and marketing beer and other beverages across hundreds of brands, including Budweiser, Stella Artois and Corona. Operates a vast global supply chain and retail network serving consumers worldwide.

Industry: Food & Beverage

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Leuven, Belgium

Founded: 2008

Website LinkedIn

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Anheuser-Busch InBev

2 weeks ago

Manager Machine Learning Platform - Bees Data

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Campinas

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Lead a team responsible for building and scaling BEES’s Machine Learning Platform for production ML systems.
•Translate ML strategy into a platform roadmap balancing business priorities, reliability, developer experience, cost efficiency, and long-term architecture.
•Own execution across MLOps, model development workflows, model serving, infrastructure, reliability, observability, governance, and developer experience.
•Drive end-to-end delivery of reusable platform capabilities (ML pipelines, experiment tracking, model registries, feature/data workflows, training infrastructure, inference services, monitoring, alerting, governance).
•Establish engineering standards and paved paths (CI/CD, testing, versioning, reproducibility, release management, rollback strategies, documentation, operational readiness) and drive SLO/SLA-based operational excellence.

Pay and Benefits

Perks:Annual BonusHealth InsuranceDentalLife InsurancePensionMeal AllowanceDays OffCommuter BenefitsChildcareLearning Budget

Key Requirements

•Bachelor’s degree in computer science, engineering, mathematics, or another quantitative field (or equivalent practical experience), with a master’s degree a plus.
•Experience managing or technically leading engineering teams building production ML/data/developer platforms, distributed systems, or cloud infrastructure.
•Strong understanding of the ML lifecycle, including data preparation, feature engineering, experimentation, training, evaluation, packaging, deployment, serving, monitoring, retraining, and governance.
•Ability to lead across multiple ML platform disciplines, including MLOps, model development workflows, model serving, infrastructure, reliability, observability, and platform governance.
•Technical credibility with modern ML platform and cloud-native technologies (e.g., Python, SQL, PySpark, Kubernetes, Databricks, Terraform, Azure DevOps/Git CI/CD, Azure Cloud).

Education:Bachelor's

Skills:LeadershipCommunicationStakeholder managementSystems thinkingStrategic prioritization

Languages:English

Company Brief

Anheuser-Busch InBev

Industry: Food & Beverage

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Leuven, Belgium

Founded: 2008

Website LinkedIn