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MLOps Team Lead

Fetcherr·ישראל·en
במקום העבודהמשרה מלאהAI EngineeringEnterprise SoftwareData Infrastructure

Lead a small team of MLOps engineers building and operating an internal machine learning platform for research workflows and production model pipelines. This hands-on role combines technical leadership, team development, infrastructure ownership, and software engineering.

תחומי אחריות

  • Lead, mentor, and develop a team of MLOps engineers while owning delivery and technical quality.
  • Own infrastructure and pipeline initiatives from design through production.
  • Contribute to system design and code, review implementation, and establish engineering standards.
  • Drive milestones for machine learning model lifecycle and infrastructure ownership.
  • Partner with research and other stakeholders to convert requirements into robust, scalable systems.
  • Build and maintain models and data pipelines supporting data science workflows.
  • Ensure the accuracy, consistency, and efficiency of training and inference data across structured and unstructured sources.
  • Evolve the machine learning platform, including migration from Dask to Ray.

דרישות

  • Bachelor’s or master’s degree in computer science, mathematics, engineering, or a related field.
  • At least 5 years of commercial Python experience.
  • At least 3 years of hands-on commercial MLOps experience in production.
  • Experience managing or leading engineering teams, including responsibility for people and delivery.
  • Hands-on ownership of the machine learning model lifecycle, including training, deployment, monitoring, and retraining.
  • Experience with pipeline orchestrators such as Dagster or Airflow.
  • Experience with a major cloud provider such as GCP, AWS, or Azure.
  • Experience with distributed computing systems, Docker, and Kubernetes.
  • Commercial experience developing and maintaining scalable machine learning systems.
  • Fluent written and spoken English.

יתרון

  • Experience with Dagster, Dask, Ray, or Spark.
  • Experience implementing distributed algorithms in Python.
  • Background in predictive, forecasting, or pricing-optimization machine learning systems.
  • Experience in aviation, demand forecasting, or price optimization.
  • Strong understanding of data structures and algorithms.

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