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EPAM Systems

Senior AI Engineer

Posted Updated
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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

Benefits

  • 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

Skills

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