Principal Machine Learning Engineer

Bunge Iberica SA; São Paulo; Presencial; BRL 279 000 - 390 600; Tempo integral

Resumo da oferta

A multinational food company is seeking a Principal Machine Learning Engineer in São Paulo, Brazil. The role requires strong experience deploying machine learning solutions using Google Cloud Platform and a commitment to best practices in DevOps. You will work with data scientists on scaling algorithms and building large-scale data infrastructure. The ideal candidate has a bachelor's degree in Computer Science and at least 5 years of hands-on DevOps engineering experience. Fluency in English is required.

Qualificações

• 5+ years of experience in DevOps engineering with cloud services, preferably GCP.
• Experience mentoring junior engineers and technical consulting for product managers.
• Ability to apply software development best practices to machine learning projects.

Responsabilidades

• Collaborate with Data Scientists on scaling algorithms and industrializing solutions.
• Build and maintain the large-scale data infrastructure for AI projects.
• Develop CI/CD pipelines and deployment infrastructure using GCP.

Conhecimentos

GCP (Google Cloud Platform)

DevOps Engineering

Kubernetes

Docker

Python

Formação académica

Bachelor’s degree in Computer Science or related field

Ferramentas

Google Cloud Services

Datadog

Prometheus

Grafana

Descrição da oferta de emprego

Principal Machine Learning Engineer

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

Essential Functions

• Collaborate with Data Scientists to test and scale new algorithms through pilots and industrialize 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 end‑to‑end solutions.
• Leverage software architecture and design patterns to write scalable, maintainable, 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 framework and tools to improve data quality.
• Work in cross‑functional agile teams of 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 delivering the team mission and accepted backlog.
• Partner with Software Development, Data Science and DevOps to understand their requirements and build well‑architected automated solutions, such as CI/CD pipelines or deployment infrastructure using Google Cloud Platform.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology or related field, or equivalent work experience.
• At least 5 years of proven, hands‑on DevOps engineering experience with major public cloud services, preferring GCP services (Compute Engine, GKE, BigQuery, Cloud Run, Cloud Composer). Google Cloud Professional certifications (Architect, Data Engineer, or DevOps) are a plus.
• Experience developing and mentoring junior engineers, acting as a technical consultant to product managers and stakeholders.
• Ability to apply software development best practices to machine learning projects, including unit testing, DevOps integration, release management, and test‑driven development.
• Proficiency in Kubernetes, Docker, and container orchestration.
• Experience building large‑scale monitoring solutions on Google Cloud Monitoring, Datadog, Prometheus, Grafana, or similar.
• Knowledge of Python and scripting languages (e.g., Bash). Experience with Spark or other big‑data technologies is a plus.
• Strong understanding of Agile and Scrum methodologies and ability to keep the team focused on delivering business value.
• Self‑motivated, strong problem‑solving and learning skills, with flexibility to adapt to changes.
• Fluency in English.