MLOps Engineer (AI)

TL;DR

MLOps Engineer (AI): Building and operating large-scale, production-grade machine learning systems with an accent on end-to-end ML pipelines, data consistency, and infrastructure automation. Focus on designing reproducible workflows, optimizing system reliability, and scaling ML infrastructure for real-time data-driven decision-making.

Location: Tel Aviv

Company

hirify.global is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions, currently expanding its Large Market Model (LMM) technology across multiple industries.

What you will do

• Build and operate end-to-end ML pipelines supporting training, validation, deployment, and monitoring.
• Design automated, reproducible ML workflows using CI/CD and infrastructure-as-code.
• Create and maintain complex data pipelines for large-scale ML workloads.
• Implement model versioning, experiment tracking, and feature engineering workflows.
• Monitor model performance, data drift, and system health while enabling automated retraining.
• Collaborate with ML engineers to transition research into reliable, scalable production systems.

Requirements

• 5+ years of experience building production-grade systems with a strong focus on Python.
• 3+ years of experience in data engineering with large-scale data pipelines.
• Solid understanding of ML systems in production and MLOps best practices.
• Experience with distributed computing systems (Dask preferred).
• Proficiency with pipeline orchestration frameworks such as Dagster, Prefect, or Airflow.
• Strong skills in containerized environments like Docker and Kubernetes.
• Fluent English (written and spoken) required.