ai engineer for AI solutions

HireHi

Berlin

Hybrid

EUR 40.000 - 65.000

Teilzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden
Bewerbungsgenerator

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Benefits dieser Stelle

Part-time 30h/wk
30 дней отпуска
Гибкий график
Home-office
Рабочее место за границей
Современный офис
Социальные льготы
Кухня/барista
Возможности обучения
Детская помощь
Доп. отпуска

Zusammenfassung

GEMA в Берлине ищет специалиста по ИИ для разработки и внедрения ML/LLM решений, проведения анализа данных и подготовки моделей к эксплуатации. Командой занимаются эксперты, продакт-оунера и инженеры данных. Роль предполагает гибридный график и работу в современном офисе.

Кандидат должен иметь опыт разработки AI-приложений, владение Python и ML-библиотеками, а также уверенное владение немецким языком на уровне делового общения и хорошее знание английского.

Qualifikationen

  • Имеется нескольких лет опыта разработки приложений на данных или ИИ

Aufgaben

  • Определять случаи использования ИИ с экспертами и командами
  • Уточнять бизнес-вопросы и разрабатывать жизнесподобные подходы
  • Работать на всем цикле AI-доставки от анализа данных до внедрения сервисов
  • Выбор подходов ML/Deep Learning/LLM в зависимости от задачи
  • Вносить готовые решения в продукцию с учётом мониторинга и качества моделей
  • Развивать AI-платформу в команде: компоненты MLOps, мониторинг, оценка
  • Взять на себя руководство проектами и взаимодействовать с экспертами, продакт-оунерами, инженерами

Kenntnisse

Python
ML workflows
Data analysis
Feature engineering
Model training
German communication
English communication
CI/CD
MLOps
Clean Code

Tools

Pandas
NumPy
Scikit-Learn
PyTorch
TensorFlow
XGBoost
Git
CI/CD tools

Jobbeschreibung

Описание:

GEMA works to ensure that creative professionals receive a fair share of the revenue generated by the use of their musical works, allowing them to focus on their artistic work.

Задачи:
  • Identify AI use cases with subject-matter experts, Product Owners, and technical teams
  • refine business questions, and develop viable approaches, including demos or prototypes where useful
  • Work across the AI delivery lifecycle, from data analysis and feature engineering through model development, training, evaluation, and integration into usable services
  • Select classical machine learning, deep learning, neural networks, LLM-based solutions, or a practical combination based on each use case
  • Bring successful approaches into production-ready or production environments and consider deployment, monitoring, model and data quality, security, traceability, and maintainability from the start
  • Contribute to and develop the AI Platform with the team, including components for MLOps, monitoring, labeling, evaluation, and deployment
  • Take ownership of projects and work packages and collaborate closely with subject-matter experts, Product Owners, Software Engineers, and Data Engineers
Требования:
  • Have several years of experience developing data- or AI-related applications and be able to advance AI solutions from initial concept to usable application
  • Work independently and responsibly, and drive complex topics with a clear focus on results
  • Explain complex technical topics clearly, justify solution approaches and model decisions, and present results confidently to business and technical stakeholders
  • Be familiar with machine-learning and data-science workflows, including data analysis, feature engineering, model training, evaluation, and understanding model limitations
  • Use Python and libraries or frameworks such as Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, and XGBoost, or comparable tools; assess classical ML, deep learning, and generative AI approaches for each use case
  • Apply software engineering practices including Clean Code, testing, Git, Pull Requests, CI/CD, technical documentation, and maintainable architectures
  • Have experience with cloud and MLOps topics
  • Communicate confidently and precisely in German, both spoken and written, and use English confidently in a professional environment
  • Будет плюсом: Google Cloud, Infrastructure as Code, GitHub Actions, model versioning, pipeline orchestration, monitoring, deployment of ML services
Условия:
  • Part-time option: 30 hours per week
  • 30 Days of vacation
  • flexitime
  • a home-office arrangement
  • workation
  • Subsidized company restaurant
  • barista bar
  • modern office in a prime location
  • capital-forming benefits
  • discounts
  • other allowances
  • Childcare subsidy
  • active breaks
  • pme family service
  • special leave
  • flexible working arrangements
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