Senior AI Engineer
Hace 3 días
Argentina
EPAM Systems
Jornada completa
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We are looking for a Senior AI Engineer to own the end-to-end lifecycle of machine learning systems, from problem formulation to production deployment. You will design scalable ML architectures, build robust pipelines, and collaborate across teams to deliver impactful AI-driven solutions.
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 machine learning engineering or a related field
• Expertise in MLOps practices for managing the ML lifecycle
• Proficiency in PySpark and Python for building scalable data and ML pipelines
• Background in designing and deploying production-grade ML systems
• Understanding of batch and real-time data processing architectures
• Experience working with large-scale structured and unstructured datasets
• English proficiency at B2 level or higher Nice to have
• Familiarity with Apache Kafka and MLflow
• Knowledge of Machine Learning and 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
• 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 machine learning engineering or a related field
• Expertise in MLOps practices for managing the ML lifecycle
• Proficiency in PySpark and Python for building scalable data and ML pipelines
• Background in designing and deploying production-grade ML systems
• Understanding of batch and real-time data processing architectures
• Experience working with large-scale structured and unstructured datasets
• English proficiency at B2 level or higher Nice to have
• Familiarity with Apache Kafka and MLflow
• Knowledge of Machine Learning and 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