Machine Learning Engineer | Senior

Accountabilities

• Industrialize the core machine learning model of a Voice of the Customer platform, moving models from experimentation into reliable production environments.

• Transform notebook-based machine learning solutions into scalable, parametrized, and production-ready pipelines on AWS.

• Structure and maintain the MLOps lifecycle, ensuring robust model versioning, reproducibility, governance, and experiment management.

• Develop and manage training and inference pipelines using Amazon SageMaker, including Jobs, Pipelines, Model Registry, and GPU-based workloads.

• Perform statistical validation to ensure score parity and consistency between existing models and their production-migrated versions.

• Contribute to the evolution of a VoC platform that integrates data from multiple channels to generate meaningful business insights.

• Collaborate across technical and analytical initiatives to improve the reliability, scalability, and operational maturity of machine learning solutions.

Requirements:

• Proven professional experience developing and deploying machine learning solutions using Python in production environments.

• Strong experience with PyTorch and hands-on development of machine learning models.

• Practical experience with AWS SageMaker, including Jobs, Pipelines, Model Registry, and GPU-based workloads.

• Solid understanding of MLOps practices, including model and experiment versioning, reproducibility, deployment, and governance.

• Experience with statistical validation and model comparison, with the ability to assess model consistency and performance rigorously.

• Strong analytical and problem-solving skills, with a hands-on approach to investigating technical challenges and improving ML systems.

• Experience with PyTorch Geometric and Graph Neural Networks (GNNs) is a plus.

• Knowledge of NetworkX, scikit-learn, and FAISS is considered an advantage.

• Experience with machine learning model explainability is a plus.

• Ability to work collaboratively in a technically sophisticated, AI-focused environment while maintaining strong ownership of deliverables.

Benefits:

• Remote work opportunity within Brazil.

• Opportunity to work on the industrialization and scaling of production machine learning models.

• Hands-on exposure to AWS, SageMaker, PyTorch, MLOps, and modern AI engineering practices.

• Opportunity to contribute to a Voice of the Customer platform that transforms multi-channel data into business insights.

• Environment focused on Artificial Intelligence, Generative AI, advanced technologies, and digital transformation.

• Access to AI-driven tools and cutting-edge technologies supporting the development of digital-native platforms.

• Opportunities for continuous learning, knowledge sharing, and exposure to evolving technology trends.

• Strong potential for personal and professional growth in a technology-driven environment.

• Opportunity to collaborate with talented, multidisciplinary professionals on impactful AI initiatives.