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6 часов назад

Member Of Technical Staff, Machine Learning (AI)

Формат работы
remote (только United_kingdom)
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR

Member of Technical Staff, Machine Learning (AI): Building core ML components for a proactive AI chat app with an accent on high reliability for long-running workflows and real-world task completion. Focus on fine-tuning models, implementing evaluation systems, and debugging production ML systems under latency and cost constraints.

Location: Remote (United Kingdom)

Company

hirify.global is developing a proactive AI chat application designed to bring intelligence to everyday conversations and workflows.

What you will do

  • Develop and optimize ML components across data collection, training, evaluation, and inference.
  • Fine-tune and adapt neural models within larger production systems.
  • Implement rigorous evaluation and testing frameworks to analyze model behavior.
  • Build and maintain data pipelines for both real-world and synthetic datasets.
  • Debug production incidents, performance bottlenecks, and model-specific issues.
  • Iterate on features based on real user feedback under production constraints like latency, cost, and safety.

Requirements

  • Strong foundation in machine learning and modern neural architectures.
  • Hands-on experience in training, fine-tuning, or deploying ML models.
  • Proficiency in writing production-quality code.
  • Must be based in the United Kingdom
  • Ability to work through ambiguity and execute independently.

Culture & Benefits

  • High talent density environment with a world-class, small team.
  • Collaborative decision-making process and rapid shipping pace.
  • Balance between delivering high-quality work and continuous learning.
  • Focus on creating a "magical" product for billions of users.

Hiring process

  • Technical evaluation of applications by team members.
  • 3 to 4 interviews conducted via virtual meetings or onsite.
  • Prompt decision-making process and transparent feedback.

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