Machine Learning Engineer

Topaz

Machine Learning Engineer combating cyber crimes and preventing money laundering at Topaz. Responsible for deploying and monitoring machine learning models with operational excellence and scalability.

Posted 6/1/2026full-timeIndaiatuba • 🇧🇷 BrazilMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSDockerDynamoDBEC2GrafanaKubernetesMongoDBNoSQLNumpyPandasPythonTerraform

About the role

Key responsibilities & impact

We are seeking a Machine Learning Engineer (MLOps) to join our data team to help combat cybercrime and prevent money laundering.
You will be responsible for ensuring our machine learning models are deployed, monitored, and maintained in production with operational excellence, scalability, and reliability.
Develop and maintain automated ML pipelines (CI/CD) for model training, validation, and deployment
Adapt data transformation pipelines for machine learning model inference
Ensure scalability and availability of ML applications in production environments
Collaborate with Data Scientists to build robust, scalable pipelines
Deploy continuous monitoring systems for model performance in production
Identify and mitigate performance degradation, data drift, and concept drift
Establish alerts and dashboards to track critical metrics (Grafana or similar)
Implement automated retraining strategies and model versioning
Update models with new data while maintaining traceability and governance
Provide infrastructure for explainability techniques (XAI), ensuring transparency and regulatory compliance
Explore and evaluate new MLOps technologies, frameworks, and tools

Requirements

What you’ll need

Minimum of 5 years of software development experience
Minimum of 3 years of data-related experience in MLOps or Data Science activities
Proficiency in Python for developing robust applications
Code versioning with Git
Strong knowledge of data structures, algorithms, and design patterns
Data manipulation with NumPy and Pandas
Unit testing with pytest
Load testing with Locust
Hands-on experience with AWS (EC2, S3, Lambda, ECR, ECS/EKS)
Containerization with Docker
Orchestration with Kubernetes
Infrastructure as Code with Terraform
Experience with GitLab CI/CD for pipeline automation
Knowledge of DevOps practices applied to ML
Experience with NoSQL databases (MongoDB, DocumentDB, DynamoDB)
ORM model development for relational databases
AWS certifications (Solutions Architect, Machine Learning Specialty) are a plus

Benefits

Comp & perks

🌱 Comprehensive Well-being: Your well-being matters. We take care of you and your loved ones with comprehensive health plans because a healthy team is a team that transforms.
🚀 Growth and Development: Your career doesn't stop. At Topaz, #Growth is constant. Through training programs and daily challenges, we provide you with the tools so your potential has no limits.
⚖️ Flexibility and Balance: We believe in balance. Enjoy the flexibility you need to do your best with our hybrid work model and a day off on your birthday to celebrate as you deserve.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Machine LearningMLOpsPythonCI/CDData manipulationUnit testingLoad testingContainerizationOrchestrationInfrastructure as Code

Soft Skills

CollaborationProblem-solvingAdaptabilityCommunicationOperational excellence

Certifications

AWS Solutions ArchitectAWS Machine Learning Specialty