Lead AI Engineer

About the Position

We are seeking a Lead AI Engineer to drive end-to-end ML delivery, from problem framing and data sourcing to deployment and monitoring. You will design scalable batch and real-time ML architectures, ship production-grade models across multiple use cases, and partner with engineering, product, and business stakeholders to define KPIs and outcomes.

Responsibilities

• Lead the full ML system lifecycle: problem formulation, data collection, feature engineering, model training, evaluation, deployment, and monitoring
• Design and implement scalable ML architectures that support batch and real-time pipelines
• Handle large-scale structured and unstructured datasets including clickstream, transactional, text, and image data
• Build and ship models such as recommendation systems, ranking models, forecasting models, and classification/regression systems
• Apply deep learning methods including neural networks, transformers, and representation learning when appropriate
• Create and maintain feature stores, model registries, and experiment tracking systems
• Ensure production readiness by optimizing latency, scalability, reliability, and cost efficiency
• Partner with engineering, product, and business teams to define KPIs and success metrics

Requirements

• 5+ years of experience building and deploying ML systems in production environments
• Hands-on expertise designing scalable ML architectures, including batch and real-time pipelines
• Strong ability to work with large-scale structured and unstructured datasets, including clickstream, transactional, text, and image data
• Demonstrated experience developing recommendation systems, ranking models, forecasting models, and classification/regression systems
• Deep understanding of deep learning techniques including neural networks, transformers, and representation learning
• Practical skills building and maintaining feature stores, model registries, and experiment tracking systems
• Solid knowledge of production readiness topics such as latency optimization, scalability, reliability, and cost efficiency
• Proven collaboration skills with engineering, product, and business teams to define KPIs and success metrics
• English proficiency at B2 (Upper-Intermediate) level or higher

Skills

• Data Science
• MLOps
• PySpark
• Python
• Apache Kafka
• MLflow
• Machine Learning
• PyTorch

We Offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling, and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek, and LinkedIn

Locations

• Argentina
• Brazil
• Chile
• Colombia
• Mexico

Note: Remote work is available for these locations.