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обновлено 5 дней назад

Applied AI Engineer

Формат работы
remote (только Switzerland)
Тип работы
fulltime
Английский
b2
Страна
Switzerland
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
Applied AI Engineer (Python/LLMs): Building and shipping AI features from models through production systems to user experiences, with an accent on agent workflows, persistent context, and reliable real-world task completion. Focus on designing evaluations, debugging across model and infrastructure layers, and optimizing latency, cost, and production reliability.

Location: Remote, Zurich, Switzerland

Company

hirify.global is building proactive AI-native applications that help users manage conversations, errands, organization, and workflows with minimal prompting.

What you will do

  • Build and ship AI features end-to-end, from model capabilities through production systems and user experience.
  • Design and iterate on prompts, tools, memory, and agent workflows.
  • Transform raw model outputs into structured, reliable, and predictable behaviors.
  • Debug issues across models, orchestration, infrastructure, and UX.
  • Optimize AI systems for latency, cost, accuracy, and production reliability.
  • Develop evaluation frameworks and collaborate with product, engineering, and research teams to improve ML-powered features.

Requirements

  • Strong foundation in machine learning and modern neural network architectures.
  • Hands-on experience training, fine-tuning, or deploying ML models.
  • Production-quality Python development skills.
  • Experience with PyTorch or JAX, LLMs, inference or serving systems such as vLLM, and vector databases.
  • Ability to work across model, infrastructure, and product abstraction layers in ambiguous, fast-moving environments.

Culture & Benefits

  • Work with a small, high-performing team building practical AI products for users worldwide.
  • Make decisions collectively while moving quickly and balancing quality with learning.
  • Operate with structure, independent judgment, and a strong bias toward shipping and continuous improvement.
  • Interviews are conducted via virtual meetings and/or onsite, with a process of three to four interviews.
  • Expect a prompt hiring decision after the evaluation.

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