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Empresa confidencial

Senior Machine Learning Engineer

RemotaNão informadoSão Paulo / SP
Publicação
16 de set. de 2026
Última verificação
16 de set. de 2026
Fonte responsável
Empregando Brasil

Sobre a vaga

This position is listed on behalf of a partner company, who manages all applications and next steps. Local São Paulo - SP Remoto

Responsabilidades

Lead MLOps initiatives covering model training, deployment, serving, monitoring, lifecycle management, and governance for production Machine Learning solutions. Develop and maintain ETL/ELT pipelines, DAGs, data workflows, and Machine Learning workflows using PySpark and distributed processing technologies. Design and manage enterprise Feature Stores, ensuring feature versioning, lineage, consistency between training and inference, and reliable point-in-time lookups.

Develop, validate, deploy, and operationalize Machine Learning models across different analytical use cases, supporting their transition from experimentation to production. Implement model versioning, Champion/Challenger strategies, rollouts, model promotion processes, and Model Registry management. Ensure quality, traceability, reproducibility, auditability, and governance across data, features, pipelines, and models, including monitoring for data, concept, and performance drift.

Design and implement CI/CD processes and Infrastructure as Code for Machine Learning platforms and manage DEV, QA, and PROD environments. Define architectural standards, MLOps guidelines, engineering best practices, automated testing approaches, and sustainable development patterns. Conduct code reviews, support Data Scientists in industrializing ML solutions, contribute to architectural decisions, and help drive the continuous evolution of the ML platform.

Maintain clear technical, architectural, and operational documentation while promoting knowledge sharing across teams.

Requisitos

Advanced experience with Databricks, including MLflow, Unity Catalog, Delta Lake, Databricks Workflows, Model Registry, Model Serving, and Databricks Asset Bundles (DABs). Strong experience developing, operationalizing, monitoring, and supporting Machine Learning models in production environments. Solid knowledge of Feature Engineering, hyperparameter optimization, model evaluation, and supervised and unsupervised learning algorithms.

Practical experience with enterprise Feature Stores, including feature versioning, lineage, consistency, and point-in-time lookups. Knowledge of Data Drift, Concept Drift, Performance Drift, and observability practices for data and Machine Learning pipelines. Strong proficiency in Python, PySpark, SQL, MLflow, Spark MLlib, and relevant Machine Learning ecosystem libraries. Experience with distributed processing and Spark workload optimization, including the ability to design efficient and scalable data workflows.

Experience building CI/CD pipelines, managing multiple deployment environments, and implementing Infrastructure as Code. Experience implementing automated testing for data pipelines and Machine Learning workflows. Knowledge of secure credential and secrets management using Service Principals, Key Vault, or equivalent solutions. Experience with Azure DevOps or equivalent development and delivery platforms.

Intermediate English proficiency, with the ability to interact with global teams and produce technical documentation in English.

Benefícios

Healthcare: Health and dental insurance. Food Allowances: Meal and food allowances. Family Support: Childcare assistance and extended paternity leave. Wellness: Access to gyms and health and wellness professionals through Wellhub and TotalPass. Profit Sharing: Profit Sharing and Results Participation (PLR). Insurance: Life insurance coverage. Continuous Learning: Access to a continuous learning platform and partnerships with online learning providers. Language Development: Language learning platform.

Discounts: Access to a discount club. Well - Being: Free online resources dedicated to physical, mental, and overall well-being. Parenting Support: Pregnancy and responsible parenting course. Inclusive Environment: Dedicated health and well-being resources, inclusion specialists, and affinity groups supporting employees throughout their journey. Accessibility Support: Support and accommodations are available for professionals with disabilities throughout the selection process.

Sobre A Empresa: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.

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Fonte: Empregando Brasil

Vaga de Senior Machine Learning Engineer em remota | Empresa confidencial