Question
2-5

MLops Engineer

3/15/2026

The MLOps Engineer will be responsible for building and owning the MLOps domain, establishing the foundations for AI infrastructure across the organization. This includes defining the architecture, tooling, and workflows necessary to support AI capabilities in an on-prem environment.

Working Hours

40 hours/week

Company Size

501-1,000 employees

Language

English

Visa Sponsorship

No

About The Company
Public Safety
About the Role

Paragon is on a mission to transform the world of cyber intelligence.

Based in Tel Aviv, Paragon’s team is made up of top-tier talent who are passionate about making an impact. At Paragon, you’ll find the freedom to think boldly, collaborate with purpose, and grow alongside a team united by a shared mission: striving for excellence, and always looking out for one another.


We are looking for our first MLOps Engineer to establish and lead the company’s AI infrastructure. We are in the early stages of AI adoption, focused on building the core systems and processes that will support future growth and advanced AI initiatives.

This foundational role is for someone excited to shape AI infrastructure in an on-prem environment, defining the technologies, architecture, and workflows that will enable AI adoption across the organization.

You will combine hands-on engineering with product thinking to design, prioritize, and implement our AI solutions.



Responsibilities

  • Build and own the MLOps domain at Paragon- establishing the foundations for AI infrastructure across the organization.
  • Define the architecture, tooling, and workflows required to support AI capabilities in an on-prem environment.
  • Evaluate and introduce relevant AI infrastructure technologies that fit our constraints and operational model.
  • Translate organizational needs into a technical roadmap and backlog for AI infrastructure development.
  • Design and implement infrastructure for running, serving, and managing AI models and AI-powered systems.
  • Collaborate with engineering and infrastructure teams to integrate AI capabilities into existing systems.

Requirements

  • Proven experience working in MLOps, AI infrastructure, or similar platform engineering roles.
  • Strong hands-on experience with on-prem environments.
  • Experience building or operating infrastructure that supports ML/AI workloads.
  • Solid background in DevOps / platform engineering tools (containers, orchestration platforms, CI/CD, observability, etc.).
  • Ability to take ownership of a new domain and build it from scratch.
  • Strong systems thinking and the ability to translate product needs into technical infrastructure.
Key Skills
MLOpsAI InfrastructureOn-Prem EnvironmentsToolingWorkflowsAI ModelsCI/CDContainersOrchestration PlatformsObservabilityPlatform EngineeringDevOps
Categories
TechnologySoftwareEngineeringData & AnalyticsScience & Research
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