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Director of Data Science

Fetcherr·Израиль·en
В офисеПолная занятостьData ScienceEnterprise Software

Lead the production engineering organization behind large-scale AI models, overseeing MLOps, machine learning engineering, data engineering, and the full model lifecycle from data pipelines through production monitoring.

Обязанности

  • Set priorities and review technical trade-offs across MLOps, machine learning engineering, and data engineering.
  • Manage functional leads and hold teams accountable for commitments and delivery dates.
  • Own production reliability, incident response, and delivery execution.
  • Oversee infrastructure for model training, serving, and large-scale data processing, including costs.
  • Define, track, and report organizational KPIs.
  • Report progress and risks to senior management, product, and commercial teams.
  • Partner with applied research to move results into production.
  • Hire senior engineers and determine organizational staffing.
  • Establish engineering standards for CI/CD, automated testing, observability, and model monitoring.

Требования

  • 8+ years of engineering experience, including 5+ years leading teams and managers.
  • Experience leading projects across multiple groups with interdependent delivery.
  • Production experience with time-series forecasting, reinforcement learning, or large-scale optimization.
  • Experience setting direction for a machine learning or data engineering organization.
  • Strong understanding of production machine learning systems and architecture review.
  • Experience managing delivery commitments, team performance metrics, and staffing.
  • Hands-on familiarity with Python, PyTorch, Google Cloud Platform, Dask, and Dagster.
  • Bachelor’s degree in computer science, engineering, mathematics, or a related field.
  • Ability to communicate technical decisions to commercial stakeholders and commercial constraints to engineering teams.

Будет плюсом

  • Master’s or PhD in computer science, machine learning, statistics, engineering, or a related field.
  • Experience taking a machine learning platform from prototype to business-critical production.
  • Experience in airlines, travel, revenue management, or dynamic pricing.
  • Familiarity with real-time inference and high-volume data processing.

Соответствие

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