MLOps Engineer

Responsibilities

• ML Pipeline Automation.
• Continuous Integration for Machine Learning projects.
• Continuous Delivery for Machine Learning projects.
• Improve and advance DataOps and MLOps infrastructure and operational processes.

Requirements

• 4+ years of industry experience in applied ML.
• Strong proficiency with Python, Scala and/or Go.
• Experience with AWS or other cloud providers.
• Experience with Jenkins or other build tools.
• Experience with ML Inference servers such as Triton, KFServing, or Seldon Core.
• Experience with Kubeflow, MLFlow or Sagemaker.

Nice to have

• Experience with infrastructure as code tools such as Terraform, Cloudformation, Ansible, Puppet or Chef.
• Experience with Kubernetes.
• Experience with Spark and/or databricks.
• Experience at the tier 1 product company or related experience working within the product organization.

Benefits include

• Getting stock options after the first year of work in the company.
• 60$ in a month for sports, medicine, trainings.
• Modern office in “dana center’’.
• Corporate events.
• Participation in conferences and trainings.
• Corporate library.
• Flexible working day.
• 27 calendar days for vacation and 5 sick days.
• The salary range for this position in Vilnius, Lithuania is 4000 - 7500 € gross per month.