About the role

AI/GenAI - ML Engineer at Quento Technologies S.A. building and maintaining scalable and efficient machine learning pipelines for various AI applications.

Responsibilities

Build and maintain scalable and efficient machine learning pipelines for data preprocessing, model training, and evaluation;
Deploy and monitor machine learning models in production environments, ensuring high performance and reliability;
Integrate Large Language Models (LLMs) and Vision Language Models (VLMs) into existing applications to enhance functionality and create new AI-enhanced features;
Develop and implement Retrieval Augmented Generation (RAG) systems for knowledge-intensive applications;
Design and build LLM-based AI agents for automation, customer support, and other interactive applications;
Experiment with and evaluate different LLM techniques, including fine-tuning, prompt engineering, and embedding generation;
Develop and maintain clear and concise documentation for models, pipelines, and APIs;
Participate in code reviews and contribute to best practices for AI development;
Monitor and analyze model performance in production, identifying areas for improvement and optimization;
research and stay up to date on the newest AI trends;
Ensuring that all activities and duties are carried out in full compliance with regulatory requirements and supporting the continued implementation of the Group Anti-Bribery and Corruption Policy.

University degree in Computer Science, Engineering, or a relevant discipline;
4+ years of experience in developing AI/GenAI solutions and deploying machine learning models in production environments;
Strong understanding of traditional machine learning algorithms and techniques (e.g., linear regression, logistic regression, decision trees, support vector machines, clustering);
Experience with AI services, including Azure OpenAI, Azure AI Search, and Azure Machine Learning, for building and deploying intelligent applications is highly desirable;
Proficiency in programming languages such as Python, and experience with machine learning libraries like scikit-learn, TensorFlow, or PyTorch;
Experience with natural language processing (NLP) and computer vision (CV) techniques;
Experience with building and deploying AI agents;
Experience with building and deploying API's;
A proactive and self-motivated approach to work;
A strong attention to detail and a commitment to quality;
Ability to work effectively in a fast-paced and collaborative environment;
A strong desire to learn;
Excellent written and verbal communication skills;
Experience and willingness to work in an international/multicultural environment;
Excellent knowledge of English language (written and verbal).