AI engineer in quantum computing

Qilimanjaro Quantum Tech

Barcelona

Hybrid

EUR 60,000 - 100,000

Full time

2 days ago
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Benefits offered by this job

Гибридный режим
Частная медицина
Гибкий график
Социальный пакет

Job summary

Qilimanjaro Quantum Tech в Барселоне ищет специалиста по адаптации и дообучению моделей в рамках разработки квантово-вычислительных рабочих процессов. Ваша работа будет связана с реализацией учебных и исследовательских задач, чтобы превратить эксперименты в практические инструменты для инженеров и ученых.

Требуется практический опыт в fine-tuning, сильные навыки программирования и работа с PyTorch. Привлекательно знание пайплайнов данных, отслеживания экспериментов и готовность работать в

Qualifications

  • Практический опыт дообучения или адаптации моделей, с примерами датасетов, методов оценки и результатов.
  • Сильные навыки программирования и практический опыт с PyTorch и инструментами обучения и вывода.
  • Опыт построения воспроизводимых пайплайнов данных и отслеживания экспериментов.
  • Владение вопросами качества данных, распределения и утечки.
  • Умение проектировать полные технические решения и сотрудничать с экспертами.
  • Интерес к квантовым вычислениям и готовность учиться.
  • Будет плюсом: кодовые модели, научное ML, данные измерений; оптимизация вывода; интеграция с инженерными инструментами; квантовое ПО/аппаратные рабочие процессы.

Responsibilities

  • Перевод инженерных задач в целевые эксперименты с базами данных и метриками.
  • Построение пайплайнов данных: сбор, очистка, аннотирование и версионирование.
  • Контроль происхождения данных, лицензий и предотвращение утечек между обучением и оценкой.
  • Тонкая настройка моделей эффективными методами под задачи и бюджет.
  • Создание повторяемых инструментов оценки точности и задержки.
  • Изучение отказов и сравнение подходов: retrieval, инструменты, простые методы.
  • Преобразование экспериментов в версионированные компоненты с документацией.
  • Сотрудничество с командами по инференсу, мониторингу и поддержке.
  • Обоснование решений и документирование экспериментов для воспроизведения.
  • Руководство стажером по задачам и код-ревью.

Skills

Fine-tuning моделей
PyTorch
Отслеживание экспериментов
Data pipelines

Tools

Python

Job description

Описание

Qilimanjaro Quantum Tech is a Barcelona-based company building full-stack analog quantum computers. Founded in 2019 as a spin-off from BSC, UB and IFAE, we bring together quantum hardware, control systems and software to make quantum computing useful in practice.

Build Qilimanjaro’s in-house capability to develop company-owned specialist AI models for engineering and quantum-computing workflows. You will adapt existing models using company knowledge and authorized data, establish whether they improve real tasks, and integrate successful results into tools used by engineers and scientists.

Задачи
  • Translate engineering needs into focused experiments with clear baselines, held-out test data and measurable acceptance criteria.
  • Build data pipelines for collection, cleaning, labeling and dataset versioning.
  • Track provenance, permitted uses and licensing, and prevent leakage between training and evaluation.
  • Fine-tune existing models, including parameter-efficient approaches, choosing methods suited to the task, available data and compute budget.
  • Build reusable evaluation tools to measure task accuracy, regressions, cost and latency.
  • Investigate failure modes and compare fine-tuning with retrieval, tool integration or simpler methods.
  • Turn validated experiments into tested, versioned components with documented interfaces.
  • Work with the relevant teams on inference, monitoring and maintenance.
  • Explain technical choices and limitations clearly, flag delivery risks early, and document experiments so colleagues can reproduce the results.
  • Guide the intern through scoped tasks, pairing and code review.
Требования
  • Hands-on experience fine-tuning or adapting models, with concrete examples of the datasets, evaluation methods and results.
  • Strong coding skills and practical experience with a modern deep-learning framework such as PyTorch and tools for model training and inference.
  • Experience building reproducible data and training pipelines, tracking experiments and maintaining tested software.
  • Sound judgment about data quality, overfitting, leakage and distribution shift, and the ability to distinguish benchmark gains from useful improvements.
  • The ability to design and deliver complete technical solutions, collaborate with domain experts and support less experienced contributors.
  • Interest in quantum computing and willingness to learn the scientific and engineering context.
  • Будет плюсом: Code models, scientific machine learning or measurement data; Inference optimization and model compression; Integration with engineering tools; Quantum software or hardware-connected workflows
Условия

Help build our in-house AI capability alongside the engineers and scientists developing quantum computers. Your work will connect specialist models with real engineering problems, with room to shape the tools and methods we use. We offer technical growth through multidisciplinary work and an established engineering career path. Career path Strong mentorship and technical growth

  • Competitive salary
  • Private health insurance
  • Cobee flexible compensation (transportation, meals, and childcare support)
  • Flexible working hours
  • Hybrid work model
  • Get the opportunity to build something amazing and unique, something that hasn't been done before
  • Work on ground-breaking projects and possibly solve massive challenges on a global scale
  • Be at the intersection of research and industry, where biggest innovations happen
  • Make an enormous impact in a dynamic scale-up rather than being a small cog in a big machine
  • Work with super smart, knowledgeable and yet, very friendly people in Barcelona, one of the best cities in the world (picture a lot of sun, amazing food and friendly locals)
  • Get to be part of a start-up where growth on a company and individual level is the default
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