Senior Machine Learning MLOps Engineer
New
BrazilFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Required Skills
- AWSPythonSQLMachine LearningCI/CDTerraformMLOps
Requirements
- Strong hands-on experience with AWS services, particularly Amazon SageMaker, S3, IAM, VPC, CloudWatch, Lambda, and Step Functions.
- Proven experience deploying machine learning models using real-time endpoints, batch processing, serverless inference, and multi-model endpoints.
- Advanced Python skills for developing training scripts, inference services, and automation workflows.
- Solid understanding of CI/CD practices and tools such as GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
- Experience with Infrastructure as Code (Terraform, CloudFormation, or AWS CDK).
- Strong SQL skills and experience handling large-scale datasets and data pipelines.
- Knowledge of model performance monitoring, including metrics related to accuracy, drift detection, latency, and throughput.
- Experience with observability and monitoring tools in production environments.
- Strong communication and collaboration skills to work effectively with data science, engineering, and infrastructure teams.
Responsibilities
- Deploy and maintain machine learning models in production environments, supporting both batch and real-time inference scenarios.
- Build, optimize, and maintain end-to-end CI/CD pipelines for machine learning workflows, from training and validation to deployment and monitoring.
- Manage and evolve Feature Store environments, including feature creation, versioning, and availability for training and inference.
- Monitor production models by tracking performance metrics such as data drift, model drift, latency, throughput, and overall system health.
- Implement model governance practices, including experiment tracking, model versioning, and registry management.
- Ensure robust observability through logging, monitoring tools, and alerting mechanisms for ML services.
- Optimize cloud infrastructure usage and costs, applying FinOps best practices across machine learning workloads.
- Collaborate closely with multidisciplinary teams to deliver scalable, secure, and business-oriented AI solutions.
- Contribute to deployment strategies, platform improvements, and the continuous evolution of MLOps capabilities.
View Full Description & ApplyYou'll be redirected to the employer's site
