Director of Data Science (AI)

Location: Netanya, Israel

Company

hirify.global develops responsible AI and a proprietary market model that delivers demand predictions and real-time decision intelligence for commercial teams, initially serving the aviation industry.

What you will do

• Lead production engineering across MLOps, ML engineering, and data engineering.
• Own the end-to-end machine learning lifecycle, including data pipelines, model training, serving, and monitoring.
• Set the roadmap, priorities, engineering standards, KPIs, and delivery expectations across functions.
• Own infrastructure for model training, serving, and large-scale data processing, including cost management.
• Work with applied research to move results into production and report progress and risks to senior, product, and commercial stakeholders.
• Hire and retain senior engineers while defining team structure and staffing.

Requirements

• 8+ years of engineering experience, including 5+ years leading teams and managers.
• Experience leading projects with inter-group dependencies and setting direction for machine learning or data engineering teams.
• Production experience with time series forecasting, reinforcement learning, or large-scale optimization.
• Strong knowledge of production ML systems and experience reviewing architecture decisions.
• Hands-on familiarity with Python, PyTorch, Google Cloud Platform, Dask, and Dagster.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, plus the ability to communicate technical and commercial constraints across audiences.

Nice to have

• MSc or PhD in Computer Science, Machine Learning, Statistics, Engineering, or a related field.
• Experience taking a machine learning platform from an early prototype to business-critical production use.
• Experience in airlines, travel, revenue management, or dynamic pricing.
• Familiarity with real-time inference and high-volume data processing.

Culture & Benefits

• Work on AI models that set prices in live commercial markets.
• Collaborate across applied research, engineering, product, commercial, and senior management functions.
• Operate in a production-focused environment with emphasis on reliability, observability, automated testing, and model monitoring.