MLOps (DevOps) Engineer

Website Oreyeon

MLOps (DevOps) Engineer:

Please read carefully the qualifications and responsibilities and include relevant skills in your CV

Oreyeon is a startup company providing AI solutions for airports focusing on safety and automation of operations. Oreyeon’s goal is to re-imagine airport safety by implementing proactive features, eliminating human error and reducing costs by using cutting-edge technologies.

We are looking for a full-time MLOps (DevOps) Engineer experienced in designing, implementing and maintaining data/ML pipelines. You should be passionate about creating new technologies and building scalable end-to-end ML workflows.

Education: Bachelors or Masters degree in Computer Science/ Software Engineering (similar technical field of study or equivalent practical experience)

Experience: 2+ years in the MLOps field


  • Work with the ML team to develop, optimize and accelerate the ML/AI lifecycle
  • Maintain a scalable infrastructure through the use of MLOps tools to automate integrate and monitor operational processes along with our data platform
  • Build and automate CI/ CD pipelines and QA systems to improve reliability, robustness and speed
  • Implement practices for monitoring, logging and alerting on cloud environments
  • Develop scalable data pipelines compatible with both the ML and production lifecycle (data flow, collection, annotation, processing, inference and analytics)
  • Implement and manage a Data Warehousing system to retrieve, update, visualize and analyze data
  • Develop set processes for data mining, data modeling, and data production
  • Identify ways to improve data reliability, efficiency and quality
  • Implement data visualization tools

Key Qualifications:

  • Experience with model implementation, monitoring and deployment on Cloud infrastructures such as AWS
  • Experience with model lifecycle management (training, deploying, storing…)
  • Experience with utilizing and integrating triggersinto ML pipelines
  • Experience with Docker and Kubernetes and familiarity with inference servers such as KFServing or Seldon Core
  • Experience with building CI/CD pipelines
  • Experienced with building, maintaining, scaling and monitoring cloud ML and data pipelines
  • Familiar with data driven development
  • Solid knowledge and proven experience in Python
  • Solid  knowledge of Data Structures and algorithms, and hands-on experience with SQL/No-SQL database design
  • Experienced with building and managing database systems

Preferred Qualifications:

  • Experienced with one or more of the following AWS tools: Sagemaker, Route53, CloudFormation, StepFunctions, Lambda, S3, SNS, SAM, API Gateway, CodeBuild, ECR, EventBridge, Puppet, Chef, Ansible, Terraform
  • Experience with one or more of the following data solutions: Spark, Hadoop, Kafka databricks
  • Solid knowledge concerning data storage, data security, data privacy and data modeling on a cloud platform

Soft Skills Required:

  • Professional writing & communication in English
  • Clear technical documentation
  • Collaboration with team members
  • Adaptability in a dynamic fast-paced environment

Please apply through our website on


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