Generative AI Engineer
2 semanas atrás
With just over 7 years of experience in the Portuguese market, we share our DNA with more than 200 workers and position our offer according to 3 lines of service:
- Strategy (Outsourcing, NeXel, Team as a Service, Tech Academies);
- R&D (Bootcamps, POC, Tech Lab);
- Nearshore.
In ADENTIS, we focus on PEOPLE. This is our emotional salary:
- Great Work-Life balance;
- Very flexible organizational routine;
- Health benefits (for you and your family);
- Team Building
activities; - Over 300 protocols to offer you great discounts in different areas;
- Continuous professional development sponsored by our Training and Certification Department;
- Regular feedback on your performance through a personalized plan;
- Comprehensive career plan and progression involving assertive performance reviews.
Responsibilities:
Develop and implement generative AI models, including LLMs and multimodal architectures, for use cases such as 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 (DE) and IT teams to identify and leverage data platforms that support the development of feature stores, pipelines, and dataset management for generative AI workloads.
Advance the MLOps/LLMOps discipline to include model versioning (model registry), dataset versioning, prompt management, and experiment tracking to support a robust experimentation environment.
Utilize Azure Databricks for data processing, model training, fine-tuning, and deployment, optimizing resources for efficient and cost-effective generative 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.
You must have:
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 twice per month.
If you want to be part of a real People First organization, join us Send your CV to
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