Live opening · Posted 10 hours ago

MLOps Engineer

Accenture Baltics · Vilnius, Vilniaus, Lithuania (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 10 hours ago
CompanyAccenture Baltics
LocationVilnius, Vilniaus, Lithuania (Remote)
Work modeYes
SkillsPython, AWS, Azure, GCP, Docker, Kubernetes, TensorFlow
SourceLinkedin
ListedPosted 10 hours ago

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About the role

Description supplied by the original job listing.

MLOps is a set of management techniques for the deep learning or production ML lifecycle, formed from machine learning or ML and operations or Ops. These include ML and DevOps methods, as well as data engineering processes for deploying and maintaining machine learning models in production.
Benefits:
Compensation at Accenture varies depending on a wide array of factors including but not limited to role, level, location, effort, responsibility, skillset, and level of experience. The range of base pay for this role is:
Senior Analyst – 1,700 - 3,400 EUR gross per month
Analyst – 1,400 - 2,800 EUR gross per month
Flexible vacation + health & travel insurance + relocation
Work from home, flexible working hours
Work with Fortune 500 companies from different industries all over the world
Skills development and training opportunities, company-paid certifications
Opportunities to advance career
An open-minded and inclusive company culture
Key responsibilities:
Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)
Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools
Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
Data science models testing, validation and tests automation
Communicate with a team of data scientists, data engineers and architect, document the processes
Required Qualifications:
Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP)
Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
Ability to understand tools used by data scientist and experience with software development and test automation
Fluent in English, good communication skills and ability to work in a team
Desired Qualifications:
Bachelor’s degree in Computer Science or Software Engineering
Experience in using AWS, MS Azure or GCP services.
Good to have any associate Cloud Certification
Due to project requirements, candidates must currently hold EU work permit and be available to start within 1 to 3 months of receiving an offer.

Work arrangement
Yes

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