Machine Learning Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Design, implement, and consistently enhance machine learning models for Zé Delivery.

• Create and manage data, feature, training, and inference pipelines at scale.

• Develop solutions for recommendation and personalization across various stages of the customer journey.

• Track the performance, quality, and stability of models in a production setting.

• Define and assess experiments, A/B tests, and impact metrics.

• Collaborate with Data, Engineering, Product, and Business teams.

• Act as a technical advisor and support the growth of junior professionals.

• Contribute to a culture at Ambev that values inclusivity, diversity, collaboration, and technology.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related discipline.

• Minimum of 5 years of experience in Machine Learning, Data Engineering, Software Engineering, or Data Science within production environments.

• Demonstrated experience in deploying and managing models in production.

• Capacity to independently oversee projects from start to finish.

• Excellent communication abilities and the skill to translate technical decisions into business outcomes.

• Extensive proficiency in Python, SQL, PySpark, and cloud platforms, particularly AWS or Azure.

• Familiarity with MLOps, encompassing 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 understanding of machine learning, statistics, software engineering, and distributed systems.

• Ability to assess models based on quality, scalability, cost, latency, and impact on business.

• Experience with two-tower models, retrieval, ranking, and embeddings.

• Familiarity with real-time recommendation systems.

• Knowledge of Kubernetes, Databricks, MLflow, Airflow, or feature stores.

• Experience in optimizing cost, latency, and scalability in cloud-based environments.

• Proven experience in technical leadership.

🏝️ Benefits

• 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