🕒 yesterday
Desenvolva e modernize a plataforma de seguros Auto Frota, atuando como referência técnica para arquitetura, implementação de microsserviços, qualidade, integração de IA e migração segura de sistemas legados.
MLOps Engineer
📅 Jul 9, 2025
MlopsDevOpsAWSSagemaker
📜 Description
- Assist in designing, implementing, and maintaining scalable MLOps pipelines on AWS using services such as SageMaker, EC2, EKS, S3, and Lambda.
- Coordinate with the platform team to troubleshoot Kubernetes clusters (EKS) for deploying machine learning models and microservices.
- Develop and maintain CI/CD pipelines for model and application deployment, testing, and monitoring.
- Collaborate with Data Science and DevOps teams to streamline the model development lifecycle from experimentation to production.
- Implement security best practices within the AWS infrastructure, including network security and data encryption.
- Monitor and optimize data and ML pipelines to ensure high availability and performance.
🛠️ Requirements
- Bachelor’s degree in Computer Science, Engineering, or related field
- 2+ years of hands-on experience in MLOps, DevOps, or related fields
- Knowledge and preferable working experience in AWS services for machine learning, such as SageMaker, EKS, S3, EC2, Lambda, and others
- Exposure to Kubernetes for container orchestration
- Experience with Docker
- Exposure to infrastructure-as-code tools such as Terraform or CloudFormation
- Familiarity with CI/CD tools such as GitLab CI
- Understanding machine learning model lifecycle
- Familiarity with monitoring and logging solutions like Prometheus, Grafana, CloudWatch and ELK Stack
- Understanding of networking concepts and cloud security best practices
✨ Benefits
- Attractive remuneration package plus performance related reward
- Intellectually stimulating work environment
- Continuous personal development and international training opportunities
Full job description
The Role:
We are looking for a skilled MLOps Engineer to join our team and play a key role in bridging the gap between our Data Science and Infrastructure teams. You will be responsible for supporting the Data Science team in MLOps-related tasks while also helping in DevOps initiatives, including CI/CD pipeline creation, provisioning of cloud resources using tools like Terraform, and Kubernetes orchestration. You will collaborate closely with data scientists and engineers to deploy data pipelines, train machine learning models, and manage their deployment within scalable cloud environments while ensuring high performance, security, and reliability throughout the ML lifecycle.
All applications will be treated with strict confidentiality!
By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.
The main responsibilities of the position include:
Main requirements:
The following will be considered an advantage:
Benefit from:
The Hiring Experience: What Awaits You
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