Generative AI Engineer — Hybrid (In-Office 1–2x/wk)

Adentis Portugal

Lisboa

Híbrido

EUR 55 000 - 85 000

Tempo integral

Há 12 dias
Gerador de candidaturas

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Vantagens oferecidas por esta oferta de emprego

Great Work-Life balance
Very flexible organizational routine
Health benefits for you and family
Continuous professional development

Resumo da oferta

Adentis Portugal is seeking a highly skilled Machine Learning Engineer/Generative AI Engineer to design and deploy AI solutions. You will collaborate with IT/DevOps, use Azure Databricks for data processing, and work on CRM-based platforms to deliver production-ready models.

The role requires strong Python expertise, experience with ML frameworks, and a background in data pipelines, model versioning, and prompt management. In-office collaboration is expected once or twice per week.

Qualificações

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • Proven experience as a Machine Learning Engineer, Generative AI Engineer, or similar role, preferably with exposure to CRM and platform-based solutions.
  • Proficiency in developing generative AI models, fine-tuning LLMs, working with embeddings, RAG techniques, and applying models for personalization, automation, and semantic understanding.
  • Experience with pipeline automation, data flow monitoring, and hands-on use of Azure Databricks for data processing, training, and deployment of generative models.
  • Familiarity with cloud infrastructure management, preferably within the Azure ecosystem, and strong programming experience with Python (and optionally R or Scala).
  • Proficiency with relevant frameworks and libraries such as Hugging Face Transformers, LangChain, PyTorch, TensorFlow, or similar tools.
  • Strong analytical and problem-solving skills, paired with excellent communication and collaboration abilities.
  • Familiarity with DevOps/LLMOps practices and tools, with experience in CRM platforms and customer data analytics considered an advantage.
  • EU Citizenship or Portuguese Working Visa / Residency.
  • Availability for in-office collaboration once or twice per week.

Responsabilidades

  • Develop and implement generative AI models, including LLMs and multimodal architectures, for content personalization, intelligent automation, semantic analysis, and assisted creation.
  • Create and manage automated data pipelines and fine-tuning workflows, ensuring efficient data processing, dataset preparation, and seamless integration of generative models into existing systems and workflows.
  • Enhance platform monitoring capabilities in alignment with the Data Science team to ensure the quality, consistency, and reliability of data used for training, evaluation, and inference of generative models.
  • Collaborate with Data Engineering and IT teams to identify and leverage data platforms that support feature stores, pipelines, and dataset management for generative AI workloads.
  • Advance the MLOps/LLMOps discipline to include model versioning, dataset versioning, prompt management, and experiment tracking.
  • Utilize Azure Databricks for data processing, model training, fine-tuning, and deployment, optimizing resources for efficient AI solutions.
  • Design and maintain scalable, high-performance infrastructure required to serve generative models in production environments.
  • Work closely with IT and DevOps teams to manage cloud resources and deployment environments, ensuring security, scalability, and performance of generative AI applications.

Conhecimentos

Generative AI
LLMs
Python
Azure ecosystem
DevOps/LLMOps
CRM platforms
Data pipelines
embeddings

Formação académica

Bachelor's or Master's in CS/DS/Engineering

Ferramentas

Azure Databricks
Hugging Face Transformers
PyTorch/TensorFlow
LangChain

Descrição da oferta de emprego

Adentis Portugal is seeking a highly skilled Machine Learning Engineer/Generative AI Engineer to design and deploy AI solutions. You will collaborate with IT/DevOps, use Azure Databricks for data processing, and work on CRM-based platforms to deliver production-ready models.

The role requires strong Python expertise, experience with ML frameworks, and a background in data pipelines, model versioning, and prompt management. In-office collaboration is expected once or twice per week.

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