Machine Learning Engineer Lead

Demonstrated leadership skills and experience in client interactions. Demonstrated work experience in roles such as Machine Learning Engineer, ML Architect or similar. In-depth understanding of AI/ML principles, including neural networks and various ML models. Familiarity with Modern Data Architectures and DevOps methodologies. Previous involvement with data processing ETL and ML workflows. Understanding of Deep Learning frameworks like Keras, PyTorch, Tensorflow. Strong grasp of Python and proficiency in at least one other strongly typed language. Knowledge of mathematical modeling and proficient statistical intuition. Experience in implementing Machine Learning-based systems and MLOps. Ability to develop strategic implementation plans. Intermediate level of English and advanced level of Spanish.

Effectively manage projects by engaging with customers to understand the scope of work. Lead teams, collaborating with Machine Learning and data engineers. Champion the productization of ML models following MLOps best practices. Collaborate with Machine Learning Engineers to develop meaningful ML Proof of Concepts (POCs). Oversee the lifecycle of Machine Learning models and optimize them as necessary. Translate business and mathematical/statistical requirements into software implementations. Explore emerging ML Engineering technologies and techniques. Participate in defining project roadmaps, timelines, and estimates. Document and disseminate industry-leading practices in AI/ML. Collaborate on hiring interview processes.