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EPAM Systems / Software

Lead AI Engineer

nuevaDesde Argentina

  • Argentina
  • Tiempo completo
  • Modalidad no informada
  • Lead
  • 5+ años de experiencia

Requisitos

  • machine learning
  • • 5+ años de experiencia
  • • inglés b2

La búsqueda

We are looking for 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

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

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