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2 дня назад

AI Engineering Lead (LLM)

Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
c1
Страна
Sweden
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

AI Engineering Lead (LLM): Building and optimizing high-performance LLM ensembles for software engineering products with an accent on model alignment, fine-tuning, and performance optimization. Focus on designing end-to-end training pipelines, scaling synthetic data generation, and leading a world-class research team to push the boundaries of code generation.

Location: On-site in Stockholm, Sweden

Company

hirify.global is a product company building a platform that enables anyone to create software using plain English, serving millions of users globally.

What you will do

  • Design and execute experiments grounded in real coding and product use cases.
  • Define, track, and optimize product-centric LLM performance metrics.
  • Own training pipelines, distillation workflows, and synthetic data generation systems.
  • Partner with engineering leads to hire and hone a world-class team.
  • Work closely with infra and product engineers to scale and ship model improvements.

Requirements

  • English: C1 proficiency required
  • Proven experience contributing to cutting-edge LLM research at top AI labs.
  • Expertise in fine-tuning large-scale transformer models on code and multimodal datasets.
  • Strong background in designing high-quality experiments and effective evaluation frameworks.
  • Demonstrated leadership experience mentoring researchers and engineers.
  • Ability to work on-site in Stockholm.

Nice to have

  • Published research at top ML/AI conferences on LLMs, code intelligence, or agentic reasoning.

Culture & Benefits

  • Work in a talent-dense, high-velocity environment.
  • Focus on extreme ownership and low-ego collaboration.
  • Opportunity to shape a generation-defining AI company.

Hiring process

  • Short form submission followed by an intro call.
  • Take-home exercise.
  • Two technical interviews.
  • Two-day on-site trial work period.

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