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Senior AI Engineer

EPAM Systems

Senior 🇬🇧 English
PySpark Python MLOps Apache Kafka MLflow PyTorch

Descripcion del puesto

About the role

We are seeking a Senior AI Engineer to own the end‑to‑end lifecycle of machine learning systems, from problem formulation through production deployment. You will design scalable architectures, build robust pipelines, and collaborate across teams to deliver impactful AI‑driven solutions.

Key responsibilities

  • Own the full ML lifecycle: 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 like recommendation systems, ranking, forecasting, and classification/regression.
  • Apply deep learning techniques, including neural networks, transformers, and representation learning.
  • 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.

Required profile

  • 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.

Required skills

  • PySpark
  • Python
  • MLOps
  • Apache Kafka (nice to have)
  • MLflow (nice to have)
  • PyTorch (nice to have)

What we offer

  • International projects with top brands and global teams.
  • Healthcare benefits and employee financial programs.
  • Paid time off, sick leave, and upskilling opportunities.
  • Unlimited access to LinkedIn Learning library (22,000+ courses).
  • Global career opportunities and volunteer/community involvement.
  • Award‑winning culture recognized by Glassdoor, Newsweek and LinkedIn.

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Publicado hace 1 semana

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