Generative AI Engineer
Job Summary
The Generative AI Engineer will develop and implement advanced AI models, including LLMs and multimodal architectures. You will manage automated data pipelines and fine-tuning workflows to integrate generative solutions into production environments. Additionally, you will collaborate with cross-functional teams to advance MLOps/LLMOps practices within the Azure ecosystem.
Responsibilities
- Develop and implement generative AI/LLM models
- Manage automated data pipelines and fine-tuning workflows
- Advance MLOps/LLMOps and model versioning
- Design scalable production infrastructure using Azure Databricks
Required Skills
- Proficiency in Python and LLM/Generative AI frameworks
- Experience with Azure Databricks and Cloud infrastructure
- Knowledge of MLOps, RAG, and fine-tuning techniques
- Strong analytical and cross-functional collaboration skills
Job Details
### 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.
### Requirements:
- 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.
- 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.
- 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.
- EU Citizenship or Portuguese Working Visa / Residency.
- Availability for in-office collaboration once or twice per week.