Machine Learning Engineer Lead

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Requirements:

• Demonstrated leadership skills and experience in client interactions.
• Proven work experience in ML Engineer, ML Architect, or similar roles.
• In-depth understanding of AI/ML principles, including neural networks and forecasting.
• Familiarity with Modern Data Architectures and DevOps methodologies.
• Previous involvement with data processing and ML workflows.
• Understanding of Deep Learning frameworks like Keras and TensorFlow.
• Strong programming skills in Python and proficiency in another language.
• Knowledge of mathematical modeling and statistical intuition.
• Experience in implementing Machine Learning-based systems and MLOps pipelines.
• Ability to develop implementation plans considering alternatives.
• English at an intermediate level and Spanish at an advanced level.

Responsibilities:

• 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 ML Proof of Concepts.
• Oversee the lifecycle of Machine Learning models, optimizing them as needed.
• Translate business and mathematical/statistical requirements into software implementations.
• Explore emerging ML Engineering technologies to enhance business value.
• Participate in defining project roadmaps, timelines, and estimates.
• Document and disseminate industry-leading practices in AI/ML.
• Collaborate on hiring interview processes.