Connecting...

W1siziisimnvbxbpbgvkx3rozw1lx2fzc2v0cy9yzwqty29tbwvyy2uvanbnl2jhbm5lci1kzwzhdwx0lwvulmpwzyjdxq

MLOps Engineer

Location: Lithuania Salary: €45 - €50 per hour
Sector: Consultancy Type: Contract
Reference #: CR/081712_1625043653

MLOps Engineer / Fully Remote / 6 months / Start ASAP

Responsibilities:

Contractors will be part of the Risk & Compliance department working in multiple countries. The main responsibility is to 1. - Help deploy and operate prioritised models to PROD 2. - Educate CoE in MLOps best practices and help draw up internal guidelines 3. - Assist in pipeline development tailoring to Risk & Compliance CoE needs together with the infrastructure department: a. CI/CD pipelines b. Scheduling c. Monitoring All this to ensure the Risk & Compliance department reaches it goals in 2021. Your main responsibility will be to build the pipelines for the statistical models utilizing the existing tech stack as well as bringing your experience into play to leverage new technologies. All tasks will be solved as part of multifunctional DevOps squads consisting of broad capabilities delivering end to end Data Science solutions. You will therefore be working closely with experienced Data Scientists and Machine Learning Operations Engineers as well as the business units who are consuming the data science services.

Requirements:

We are looking for an MLOps Engineer with a solid experience in CI/CD within Data Science and having experience in working in agile setup.

Required competences:

* Version control (Git/Bitbucket)
* CI/CD tools (Azure DevOps, Jenkins, or similar)
* Code analysis and unit testing toolkit (e.g., PyLint & PyTest, SonarQube)
* Model registry (e.g., Artifactory, MLflow)
* Workflow orchestration using Airflow or similar
* Monitoring (e.g., Prometheus, Grafana, AppDynamics)
* experience with Public Cloud (Either Azure/AWS/GCP)
* Container technologies (Docker/Kubernetes/OpenShift)
* Strong Software Engineering Background
* Linux/Bash IT Consultancy Request FORM
* Strong Python knowledge (incl PySpark)