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1 день назад

Member Of Technical Staff, Machine Learning (AI)

Формат работы
remote (только Europe)
Тип работы
fulltime
Английский
b2
Страна
Israel/Switzerland
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Member Of Technical Staff, Machine Learning (AI): Building a proactive AI smart assistant for everyday users with an accent on reliability for long-running workflows and multi-step reasoning. Focus on shipping and iterating on real-world ML components, fine-tuning models, and maintaining robust data pipelines.

Location: Remote (Zurich, Switzerland)

Company

hirify.global is a high-talent density team building a proactive AI smart assistant to bring intelligence to conversations, errands, and workflows.

What you will do

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

Requirements

  • Proficiency in Python and PyTorch or JAX.
  • Experience with production ML systems running on GPUs.
  • Strong foundations in machine learning and modern neural architectures.
  • Hands-on experience training, fine-tuning, or deploying ML models.
  • Ability to write production-quality code and navigate ambiguity.
  • Must be based in or available to work from Zurich, Switzerland

Culture & Benefits

  • High talent density environment with small, world-class teams.
  • Rapid pace of development with a balance between quality and learning.
  • Collective decision-making process.
  • Focus on executing independently and bringing structure to projects.

Hiring process

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

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