Principal Machine Learning Engineer

Bunge; São Paulo; Híbrido; BRL 300 000 - 420 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work environment

Generous PTO and benefits

Career progression opportunities

Resumo da oferta

Bunge is seeking a Principal MLE to join a global team in Sao Paulo. You will deploy ML models to production, guide data scientists and engineers, and build scalable analytics pipelines using GCP. The role emphasizes DevOps, automated pipelines, and collaboration across product and IT teams.

You will influence data infrastructure, implement end-to-end AI solutions, and maintain scalable, resilient systems while adhering to best practices and agile processes. Fluency in English is required.

Qualificações

• Bachelor’s degree in computer science, information technology, or a related field.
• Minimum 5 years hands-on DevOps experience with major public cloud services, preferably GCP (Compute Engine, GKE, BigQuery, Cloud Run, Cloud Composer).
• Experience mentoring engineers and advising product managers.
• Familiar with software development best practices: unit testing, release management, and test-driven development.
• Automation of development processes using containers, CI/CD, and orchestration tools.
• Strong knowledge of Terraform, Kubernetes and Docker.
• Experience building data‑platform products with big‑data technologies like Spark is a plus.
• Fluency in English.

Responsabilidades

• Collaborate with Data Scientists to test and scale algorithms.
• Build and maintain large-scale data infrastructure for AI projects.
• Develop scalable, well-designed code and analytical pipeline frameworks.
• Create components to address ML project pain points (model lifecycle, feature store, data quality).
• Contribute to CI/CD, data pipelines, and deployment infrastructure using Google Cloud Platform.
• Work in cross-functional agile teams to deliver AI ecosystem initiatives.
• Ensure timely delivery and alignment with team backlog.

Conhecimentos

Fluency in English

DevOps experience

Software development best practices

Agile/Scrum

Formação académica

Bachelor’s degree in CS/IT or related field

Ferramentas

GCP

Docker

Kubernetes

Terraform

CI/CD tooling

Monitoring tools (Datadog/Prometheus/Grafana)

Descrição da oferta de emprego

Location: Sao Paulo, São Paulo (BR-SP), Brazil (BR)

Requisition Number: 43238

Principal Machine Learning Engineer – Bunge. In this role you will be part of a global team working on challenging, meaningful projects impacting core business activities. Bunge is committed to operating and thriving in the digital world – creating world‑class agile teams where teammates are empowered and encouraged to collaborate and test and learn to succeed.

Overview

We are seeking GCP Machine Learning Engineers (MLE) with strong experience deploying machine learning solutions into production using state‑of‑the‑art tools, algorithms and methodologies, following DevOps and test‑driven development processes. MLEs work closely with data scientists and data engineers to guide them on model and pipeline performance, delivery stability, reproducibility, and scalability of software products.

Essential Functions

• Collaborate with Data Scientists to test and scale new algorithms through pilots and later industrialize those solutions at scale.
• Influence, build and maintain the large‑scale data infrastructure required for AI projects, and integrate with external IT infrastructure/services to provide an end‑to‑end solution.
• Leverage an understanding of software architecture and design patterns to write scalable, maintainable, well‑designed, future‑proof code.
• Design, develop and maintain the framework for analytical pipelines.
• Develop common components to address pain points in machine‑learning projects, such as model lifecycle management, feature store, and data‑quality evaluation.
• Provide input and help implement frameworks and tools to improve data quality.
• Work in cross‑functional agile teams of highly skilled software/machine‑learning engineers, data scientists, designers, product managers, and others to build the AI ecosystem within the group.
• Deliver on time, demonstrating strong commitment to deliver on the team mission and agreed backlog.
• Join forces with our Software Development, Data Science and DevOps folks to understand their requirements and build well‑architected, automated solutions such as CI/CD, data pipelines, or deployment infrastructure using Google Cloud Platform.

Qualifications

• Bachelor’s degree (or equivalent) in computer science, information technology, or a related field.
• At least 5 years proven, hands‑on DevOps engineer experience with major public cloud services, with preference to GCP (Compute Engine, GKE, BigQuery, Cloud Run, Cloud Composer). Google Cloud Professional certifications (Architect, Data Engineer, or DevOps) are a bonus.
• Experience developing and mentoring junior engineers and acting as a technical consultant to product managers and stakeholders.
• Proficiency in applying software development best practices to machine‑learning projects, including unit testing, DevOps integration, release management, and test‑driven development.
• Automation of development processes using containers, CI/CD, and orchestration tools.
• Familiar with major cloud solutions, preferably GCP, and able to recommend and select appropriate services.
• Strong understanding of software design principles and patterns.
• Ability to transform proof‑of‑concept models into scalable production solutions.
• Proficiency in Agile and Scrum methodologies, keeping the team focused on business value.
• Self‑motivated with strong problem‑solving and learning skills.
• Flexibility to changes in work direction as projects develop.
• Belief in a non‑hierarchical culture of collaboration, transparency, safety, and trust.
• Demonstrable Terraform experience.
• Experience implementing Kubernetes and Docker (or similar container engine) solutions.
• Built large‑scale monitoring solutions with Google Cloud Monitoring or other tools (e.g., Datadog, Prometheus, Grafana).
• Knowledge of Python and scripting languages (e.g., Bash). Experience building data‑platform products with big‑data technologies like Spark is a plus.
• Fluency in English.

Benefits

Bunge offers a strong compensation and benefits package, generous paid‑time‑off program, flexible work arrangements, and opportunities for career progression in a hybrid work environment that balances in‑office and remote work.