MLOps Engineer

The AI Data & Research unit is at the forefront of CyberArks innovation building data-driven ML-powered and intelligent security solutions. We are looking for a passionate MLOps Engineer to join our team of seasoned ML engineers.  

You will play a critical role in building a multi-tenant PaaS for ML pipelines and inference ensuring scalability reliability and security. You will take ownership of critical platform components drive best practices and mentor other engineers. 

• Design build and maintain infrastructure-as-code using Python and AWS services for deployment. 

• Architect build and manage Docker-based services. 

• Lead the design and implementation of solutions using AWS services such as SageMaker Lambda Step Functions SageMaker Pipelines Batch Transform and Real-Time Endpoints. 

• Enhance and maintain CI/CD pipelines (Jenkins and shared libraries). 

• Ensure multi-tenant security and tenant isolation across the platform. 

• Define and implement observability and monitoring practices with Datadog and other tools. 

• Collaborate closely with Data Scientists Data engineers MLEs Product Managers and other engineering teams to integrate ML workflows. 

• Mentor junior engineers and promote engineering best practices. 

#LI-Hybrid

#LI-OS1

Qualifications :

• Bachelors degree in computer science Software Engineering or a related field. 

• 4 years of hands-on development experience with Python and AWS. 

• Proven experience with infrastructure as code (preferably AWS CDK Terraform or CloudFormation). 

• Strong knowledge of AWS architecture and services particularly in data/ML workloads. 

• Deep experience with CI/CD pipelines (Jenkins or similar). 

• Strong expertise in Docker and containerized applications. 

• Demonstrated knowledge of cloud security scalability and tenant isolation. 

• Hands-on experience with observability platforms (preferably Datadog). 

• Self-motivated and goal-oriented with a high work ethic. 

Additional Information :

• Background in MLOps Data Platforms or Machine Learning workflows. 

• Experience with additional monitoring and logging tools (CloudWatch Prometheus ELK). 

• Leadership experience in scaling cloud-native platforms. 

• Experience in information security an advantage 

• Understanding of identity & access management secrets management or zero-trust architecture - Bonus. 

Remote Work :

No

Employment Type :

Full-time