MLOps Engineer

1 week ago

Tel Aviv, Tel Aviv, Israel Clalit Innovation Full time ₪104,000 - ₪130,878 per year

Clalit Innovation
is leading MLOps health organization focused on deploying and scaling cutting-edge machine learning solutions for generative AI (GenAI) and predictive modeling, all within our on-premises private cloud infrastructure. As we maintain our current stack and transition to a modern OpenShift-based environment and next year scale out to a public cloud, we seek talented MLOps Engineers to ensure operational excellence and drive innovation. Join us to build robust ML pipelines and support mission-critical AI systems in a collaborative, high-impact environment.

Current Tech Stack (On-Premises, to be supported during transition
):

  • MLFlow for experiment tracking
  • Docker for containerization
  • Jenkins for CI/CD
  • MSSQL for database management
  • Azure DevOps Git for version control
  • NVIDIA H200 GPUs (32 units) for accelerated computing

Target Tech Stack (On-Premises OpenShift AI on Kubernetes:

  • OpenShift Kubernetes cluster for orchestration
  • OpenShift AI for ML workflows
  • Running GenAI and predictive models
  • Integration with MSSQL and Cloudera for data management
  • Transition to public cloud planned in 1-2 years

Role Overview:

As an MLOps Engineer, you will maintain and optimize our on-premises infrastructure while facilitating the migration to an OpenShift-based private cloud environment. You'll collaborate with DevOps, DataOps, and DS teams to deploy, monitor, and scale AI models. This is a full-time role with significant growth opportunities during our tech transition.

Key Responsibilities
:

  • Design and optimize on-premises ML pipelines across current and target stacks.
  • Manage daily operations on NVIDIA GPUs, ensuring model performance and reliability.
  • Enhance CI/CD pipelines using ArgoCD and Azure DevOps in a private cloud.
  • Lead migration tasks to OpenShift K8s, focusing on AI model integrations.
  • Automate deployments and manage MSSQL/Cloudera data flows for GenAI/predictive models.

Requirements:

  • 4-7 years in MLOps/DevOps with experience in on-premises ML deployments.
  • Proficiency in Docker, Jenkins, MLFlow, Kubernetes, and MSSQL.
  • Familiarity with GPU computing (NVIDIA preferred) and Cloudera or similar big data tools.
  • Ability to mentor juniors and collaborate across teams.
  • Experience with private cloud infrastructure.

Ideal Candidate:
Versatile engineer adept at managing on-premises AI systems.

For additional details, please send your CV to:

and include that you are inquiring about "MLOps Engineer #1107"

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