7 дней назад
Engineering Team Lead (MLOps)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
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TL;DR
Engineering Team Lead (MLOps) (AI/ML platform): Building and operating an internal machine learning platform, data pipelines, and production infrastructure for multiple ML teams with an accent on model lifecycle management, scalable distributed systems, and hands-on technical leadership. Focus on leading MLOps engineers, translating research requirements into reliable systems, and migrating workloads from Dask to Ray.
Location: Netanya, Israel
Company
develops responsible AI technology for demand prediction and real-time pricing intelligence, with applications including global aviation and other volatile markets.
What you will do
- Lead, mentor, and grow a team of MLOps engineers while owning delivery and technical quality.
- Own infrastructure and pipeline initiatives for the Large Market Modeling group from design through production.
- Contribute to system design and code, review implementations, and establish engineering standards.
- Drive ML model-lifecycle and infrastructure milestones, including training, deployment, monitoring, and retraining workflows.
- Partner with R&D and stakeholders to turn research needs into robust, scalable systems.
- Evolve the machine learning platform, including the migration from Dask to Ray.
Requirements
- BSc or Master's degree in Computer Science, Mathematics, or Engineering.
- At least 5 years of commercial Python experience and at least 3 years of hands-on commercial MLOps experience in production.
- Experience managing or leading an engineering team with ownership of people and delivery.
- Hands-on experience owning the ML 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, Kubernetes, and scalable production ML systems.
- Fluent written and spoken English.
Nice to have
- Experience with Dagster.
- Experience with Dask or Ray.
- Experience with Spark, including implementing distributed algorithms in Python.
- Experience with traditional predictive, forecasting, or pricing-optimization ML systems.
- Experience in aviation, demand forecasting, or price optimization.
- Good understanding of data structures and algorithms.
Culture & Benefits
- Work in a high-growth startup environment focused on impactful AI systems.
- Build technology for pricing, forecasting, and optimization across multiple industries.
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