Machine Learning DevOps Engineer, Inc.
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  • Experience

    2-4 year
  • Salary

  • Location

    Sligo, Ireland
  • Job Function

    Machine Learning DevOps Engineer
  • Industry

    Information Technology
  • Qualification

    Degree in Computer Engineering, Degree in Computer Science

Key Skills

Java Programming, Python Programming, SQL, AWS, Apache Hadoop, Machine learning techniques, Jenkins, Google BigQuery, NoSQL, Apache Airflow, Docker, Google Cloud Platform (GCP), Kubeflow, Shell Scripting language, Linux Operating system, SMTP, HTTP acceleration

Job Description

Overstock Ireland, based in Sligo, is the European Development centre for, a technology driven online retailer.


General DevOps:

  • Administer team applications and systems on in-house machines
  • Interact with systems engineering group for external needs/dependencies
  • Work with Data Engineers to ensure data pipelines are working as intended
  • Machine Learning Related:
  • Lead MLOps efforts in architecting solutions to automate and streamline Machine Learning offline experiments and online applications
  • Lead conversations and guide decisions on putting applications in the cloud vs. on-prem
  • Aid in productionization of ML models
  • Help automate Machine Learning experimentation processes
  • Ensure that ML infrastructure is properly monitored and operational
  • Work with ML teams to troubleshoot ML server/infrastructure/systems level issues
  • Mentor and enable ML engineers to perform basic DevOps functions
  • Evaluate cloud and on-prem 3rd party tools to aid in Machine Learning experimentation/deployment

Job Requirements

  • experience with Python or similar scripting tools
  • Experience with Linux systems administration
  • Strong Linux and shell scripting experience
  • Experience with Cloud, virtualization, containers and configuration management, e.g. GCP/AWS, hypervisor concepts, Docker and Puppet
  • History showing an ability to integrate multiple disparate systems via custom scripting, automation tools (e.g. expect), etc
  • Knowledge of unique concerns related to ML development and deployment
  • Familiarity with Machine Learning experimentation lifecycle (training, evaluation, testing) and tools (e.g. Polyaxon, Kubeflow)
  • Experience with continuous integration and CI tools (such as Travis and Jenkins)
  • Familiarity with JVM environment


  • Airflow or other job scheduling systems
  • Docker
  • Kubernetes
  • Python or other scripting languages
  • SQL
  • TCP/IP and related protocols (HTTP, SMTP, SNMP, DNS, etc)
  • Hadoop and big-data systems
  • BigQuery
  • Terraform
  • NoSQL (Redis/Cassandra/etc)
  • Cloud (preferably GCP)

What you will get in return: 

A competitive salary will be offered commensurate with experience. This is a great opportunity to work as part of a collaborative and modern environment where a work life balanced is encouraged. You will receive 25 days holidays (plus public holidays), flexible/ hybrid working model, optional 9/80 work schedule, pension, full private healthcare cover for you & your spouse/ dependents, annual bonus, free onsite parking, social outings and much more. Ideally you will be based around the West of Ireland, within easy reach to our office. If you want to be part of a fun, vibrant workplace, please apply now. 


  • A Bachelor's degree in Computer Science, or equivalent

 What We Value: 

  • Life/Work Balance
  • Pride in Production
  • Trust
  • Challenge yourself, inspire others
  • Success through diversity

Equal Employment Opportunity:

It is our commitment to ensure that all employment decisions are made without regard to gender, civil status, family status, sexual orientation, age, disability, race, religion and membership of the Traveller community, (protected characteristics under the Employment Equality Acts 1998-2011).

Company Info., Inc., Inc. is an American internet retailer selling primarily furniture headquartered in Midvale, Utah, near Salt Lake City. Controversial businessman Patrick M. Byrne founded in 1999. The company initially sold exclusively surplus and returned merchandise on an online e-commerce marketplace, liquidating the inventories of at least 18 failed dot-com companies at below-wholesale prices.

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