Machine Learning Engineer

Ambev

. Develop, deploy, and continuously improve machine learning models for Zé Delivery.

Posted 9/24/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine learning models, with a strong focus on data pipelines, model performance monitoring, and technical leadership. Proficient in utilizing cloud platforms and MLOps practices to enhance recommendation and personalization solutions.

Highest-signal resume keywords

Machine LearningPythonAWSMLOpsTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData EngineeringSoftware EngineeringStatisticsModel DeploymentA/B TestingModel EvaluationRecommendation SystemsReal-Time SystemsDistributed Systems

Soft Skills

Strong CommunicationProject LeadershipCollaboration

Tools & Technologies

SQLPySparkKubernetesDatabricksMLflowAirflowCloud Platforms

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceEngineeringStatisticsMathematics

Industry Keywords

Data PipelinesFeature EngineeringBatch InferenceOnline InferenceLow-Latency Systems

Tech Stack

Tools & technologies

AirflowAWSAzureCloudKubernetesPySparkPythonSQL

About the role

Key responsibilities & impact

Develop, deploy, and continuously improve machine learning models for Zé Delivery.
Build and maintain data, feature, training, and inference pipelines at scale.
Develop recommendation and personalization solutions for different stages of the customer journey.
Monitor the performance, quality, and stability of models in production.
Define and analyze experiments, A/B tests, and impact metrics.
Partner with Data, Engineering, Product, and Business teams.
Serve as a technical reference and support the development of more junior professionals.
Contribute to an inclusive, diverse, collaborative, and technology-driven culture at Ambev.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field.
At least 5 years of experience in Machine Learning, Data Engineering, Software Engineering, or Data Science applied to production environments.
Proven experience deploying and operating models in production.
Ability to independently lead projects end to end.
Strong communication skills and the ability to translate technical decisions into business impact.
Extensive experience with Python, SQL, PySpark, and cloud platforms, especially AWS or Azure.
Knowledge of MLOps, including data and feature pipelines, CI/CD, version control, model deployment, and monitoring.
Experience with recommendation, personalization, prediction, or classification models.
Knowledge of batch and online inference, APIs, and low-latency systems.
Strong knowledge of machine learning, statistics, software engineering, and distributed systems.
Ability to evaluate models based on quality, scalability, cost, latency, and business impact.
Experience with two-tower models, retrieval, ranking, and embeddings.
Experience with real-time recommendation systems.
Knowledge of Kubernetes, Databricks, MLflow, Airflow, or feature stores.
Experience optimizing cost, latency, and scalability in cloud environments.
Experience in technical leadership.

Benefits

Comp & perks

Medical insurance
Dental insurance
Telemedicine
Life insurance
Gympass
Employee discount on company products
Christmas food basket
Toys for employees’ children
Private pension plan
Meal or food allowance
Optional transportation allowance
Attendance bonus equivalent to a 14th salary
Daycare or nanny assistance
Company profit-sharing plan
Merit-based and inclusive environment
Development and career growth opportunities within the company