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1 день назад

Senior Machine Learning Engineer (AI)

244 000 - 320 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Senior Machine Learning Engineer (AI): Building and scaling production-grade ML systems that drive real-time personalization across the hirify.global platform with an accent on real-time targeting, decisioning and personalization systems. Focus on improving system reliability, performance, and engineering efficiency.

Location: Remote (US)

Salary: $244,000 - 320,000 annually + equity + benefits

Company

hirify.global® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect.

What you will do

  • Design, build, and operate scalable machine learning systems used in real-time targeting, decisioning, personalization systems.
  • Own ML projects end-to-end, from data exploration and modeling to deployment, monitoring, and iteration.
  • Proactively safeguard model and system quality through testing, monitoring, validation, and alerting.
  • Collaborate cross-functionally with product, data, and other engineering partners to translate business problems into ML solutions.
  • Continuously improve system reliability, performance, and engineering efficiency.

Requirements

  • 6+ years of professional experience building production machine-learning software systems.
  • Proven experience owning ML systems long enough to see the downstream impact of design decisions.
  • Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or xgboost.
  • Experience with data processing and analytics tools such as pandas, Spark, SQL, and matplotlib.
  • Hands-on experience building automated pipelines for data processing, model training, validation, and deployment.
  • Strong communication skills and a high sense of ownership.

Culture & Benefits

  • Competitive perks and benefits, from health & wellness to equity.
  • Distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney.

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