We are actively seeking an experienced AI Solutions Architect / Senior AI & Machine Learning Engineer to join a technology-driven project focused on designing and implementing advanced Artificial Intelligence and Data Science solutions.

In this role, you will be responsible for defining scalable AI and Machine Learning architectures, developing and optimizing models, and deploying them into production environments. You will work across the full AI lifecycle, from data preparation, statistical modeling, and experimentation to production deployment, monitoring, and optimization.

You will collaborate with technical and business stakeholders to transform complex requirements into robust, scalable AI solutions, working with modern cloud and Big Data ecosystems. The role offers the opportunity to work with traditional Machine Learning techniques as well as emerging technologies such as Large Language Models (LLMs) and Prompt Engineering.

Core skills you’ll bring

• Strong experience designing and implementing Artificial Intelligence, Machine Learning, and Data Science architectures.

• Advanced knowledge of Machine Learning algorithms, including Decision Trees, Random Forest, SVM, K-Means, Naive Bayes, KNN, and Neural Networks.

• Strong hands-on development experience with Python and Shell Scripting.

• Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Keras, and Scikit-learn.

• Hands-on experience working with Large Language Models (LLMs) and Prompt Engineering.

• Strong knowledge of advanced statistical techniques, including statistical modeling, clustering, and predictive analytics.

• Experience developing and optimizing SQL queries.

• Experience defining data quality, control, validation, and assurance mechanisms.

• Experience deploying Machine Learning models into production environments using Docker and Kubernetes.

• Experience with Big Data and cloud ecosystems, such as Cloudera, AWS, Azure, or GCP.

• Knowledge of real-time and batch data processing.

• Experience with advanced model optimization and hyperparameter tuning.

• Availability to work under a hybrid model, attending the office three days per week.

• Availability to travel when required by business or operational needs.

Nice-to-have

• Experience designing end-to-end AI solutions across complex or large-scale environments.

• Exposure to multiple cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP).

• Experience integrating LLMs and Generative AI solutions into enterprise applications or business workflows.

• Knowledge of MLOps practices and model lifecycle management.

• Experience working with large-scale or distributed data environments such as Cloudera.

• Strong communication skills and experience collaborating with multidisciplinary technical and business teams.

The impact you'll create

• Design and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements.

• Develop, train, validate, optimize, and deploy Machine Learning models into production environments.

• Build AI solutions leveraging both traditional Machine Learning algorithms and Large Language Models.

• Define reliable data quality, validation, and control mechanisms to support AI initiatives.

• Optimize model performance through advanced statistical techniques and hyperparameter tuning.

• Support real-time and batch data processing scenarios across cloud and Big Data environments.

• Collaborate with engineering, data, and business stakeholders to translate complex challenges into production-ready AI solutions.

• Contribute to the continuous improvement and evolution of the organization's Artificial Intelligence capabilities.