Senior AI Engineer

About the Position

We are seeking a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem formulation and data collection through model training, deployment, and monitoring. This role involves designing scalable architectures and deploying production-grade models across a variety of use cases while collaborating closely with cross-functional teams.

Responsibilities

• Own end-to-end lifecycle of ML systems: problem formulation, data collection, feature engineering, model training, evaluation, deployment, and monitoring
• Design and implement scalable ML architectures including batch and real-time pipelines
• Work with large-scale structured and unstructured datasets such as clickstream, transactional, text, and image data
• Develop and deploy models such as recommendation systems, ranking models, forecasting models, and classification/regression systems
• Apply deep learning techniques including neural networks, transformers, and representation learning where appropriate
• Build and maintain feature stores, model registries, and experiment tracking systems
• Ensure production readiness through latency optimization, scalability, reliability, and cost efficiency
• Collaborate with engineering, product, and business teams to define KPIs and success metrics

Requirements

• 3+ years of experience in building and deploying ML systems in production environments
• Expertise in designing scalable ML architectures, including batch and real-time pipelines
• Proficiency in working with large-scale structured and unstructured datasets, including clickstream, transactional, text, and image data
• Experience developing recommendation systems, ranking models, forecasting models, and classification/regression systems
• Knowledge of deep learning techniques including neural networks, transformers, and representation learning
• Skills in building and maintaining feature stores, model registries, and experiment tracking systems
• Understanding of production readiness considerations such as latency optimization, scalability, reliability, and cost efficiency
• Capability to collaborate with engineering, product, and business teams to define KPIs and success metrics
• English proficiency at B2 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

About the Company

[Company description if present]