AI / ML Engineer - (LATAM CANDIDATES ONLY)

-Design, develop, and deploy machine learning and AI models to solve complex business problems.

-Build, train, evaluate, and optimize machine learning models using large and diverse datasets.

-Develop scalable data pipelines and feature engineering processes to support machine learning workflows.

-Implement and maintain production-ready ML systems, ensuring reliability, performance, and scalability.

-Integrate AI and machine learning solutions into existing applications, platforms, and APIs.

-Collaborate with data scientists, software engineers, and product teams to translate business requirements into AI solutions.

-Apply best practices for model testing, validation, monitoring, and lifecycle management.

-Implement MLOps practices including model versioning, CI/CD pipelines, automated training, and model monitoring.

-Work with cloud-based AI/ML services and infrastructure to support scalable deployments.

-Continuously evaluate and improve model performance through experimentation and tuning.

-Document models, pipelines, and workflows to ensure reproducibility and maintainability.

-Stay up to date with emerging AI and machine learning technologies and apply them when relevant.

Qualifications:

-Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field.

-4–6 years of experience developing machine learning or AI solutions in production environments.

-Strong programming skills in Python and experience with ML libraries such as TensorFlow, PyTorch, or Scikit-learn.

-Experience building and deploying machine learning models in production environments.

-Solid understanding of machine learning algorithms, model evaluation, and feature engineering techniques.

-Experience working with large datasets and data processing frameworks.

-Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

-Experience with containerization technologies such as Docker and orchestration tools like Kubernetes is a plus.

-Understanding of MLOps practices, including model monitoring, retraining strategies, and CI/CD pipelines.

-Experience working with APIs, microservices architectures, and scalable distributed systems.

-Strong analytical and problem-solving skills with the ability to translate business needs into technical solutions.

-Good communication skills and ability to collaborate with cross-functional teams.

-Advanced English proficiency skills (C1) required.