Data Science Specialist I – ML Engineering
Grupo OLX
full-time
Posted on:
Location Type: Hybrid
Location: São Paulo • 🇧🇷 Brazil
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AirflowAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPython
About the role
- Build and maintain end-to-end training pipelines, versioning, testing, and deployment of ML models
- Implement MLOps practices for automation, monitoring, and maintenance of models in production
- Manage environments, containers, GPUs, scalability, and resource orchestration
- Work in partnership with AI Scientists to turn experiments into production-ready solutions
- Ensure model observability by monitoring drift, performance, cost, logs, and metrics
- Create experimentation infrastructure and standardize AI development workflows
- Support security, governance, and best practices in model lifecycle management
Requirements
- Experience with ML/MLOps pipelines, CI/CD (GitHub Actions), and tools such as Kubeflow, MLflow, Airflow, and AWS SageMaker
- Knowledge of containers (Docker), Kubernetes, APIs, and Python
- Experience with Cloud environments (AWS, GCP, or Azure)
- Strong understanding of Machine Learning models
- Plus: Experience with large-scale data modeling and handling
- Experience with real-time / near-real-time model processing and deployment
Benefits
- Market-competitive salary
- Health insurance
- Dental plan
- Private pension plan
- Flexible benefits that adapt to your needs
- Meal allowance
- Financial counseling
- Perks club
- Home office allowance
- Mobility allowance
- Childcare assistance
- Life insurance
- Extended leave
- Incentives for sports, quality of life, and wellbeing
- Payroll-deductible loans at reduced rates
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
MLOpsmachine learningCI/CDdata modelingreal-time processingPythoncontainerizationKubernetesAPIsmodel deployment