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Lead Machine Learning Engineer (Personalization & AI Models)

EPAM·Salary not specified

Primary stack

Machine LearningTensorFlowDatabricksPythonAWSAIRedispgvectorSageMakerPyTorch

Nice to have's

ML model monitoringMLOpsCI/CDGraph Neural Networks (GNNs)real-time analytics toolsLookerTableauSnowflake

Job description

Description language:

About the Position

We are seeking a Lead Machine Learning Engineer (Personalization & AI Models) to pioneer the building and optimization of user segmentation, recommendation, and embedding models within our expansive personalization system for a Mobile App.

Remote in Ukraine: Ivano-Frankivsk

The focus areas will include multi-vector representations, real-time model inference, and the integration of personalization workflows with cutting-edge technologies including AWS Personalize SDK, PGVector, and RudderStack.

Responsibilities

  • Develop and optimize embedding models using sentence-transformer models for user profiles and personalization
  • Implement KNN-based recommendation systems for real-time content scoring and ranking
  • Utilize AWS Personalize SDK to train and deploy machine learning models that dynamically adapt to user behavior
  • Integrate embedding models with Databricks, RudderStack, and AWS services to ensure real-time profile updates
  • Fine-tune ML models aimed at boosting revenue predictions, enhancing user engagement, and refining audience segmentation
  • Optimize PGVector and Redis for efficient vector-based lookups and caching
  • Collaborate with data engineers to devise ML pipelines for robust training, validation, and deployment processes

Requirements

  • Strong experience in Machine Learning, Deep Learning, and AI-driven personalization
  • Proficiency in Python, PyTorch, and TensorFlow
  • Expertise in vector-based search and recommendation systems, including knowledge of KNN, PGVector, Redis
  • Hands-on experience with AWS Personalize SDK and SageMaker or similar ML training pipelines
  • Familiarity with Databricks, Delta Lake, and Apache Spark for large-scale model training and deployment
  • Strong understanding of real-time personalization, A/B testing, and user segmentation models
  • Capability to work with event-driven architectures and implement real-time feature engineering
  • Fluent English communication skills at a B2+ level

Nice to Have

  • Knowledge of ML model monitoring, MLOps, and automation of ML pipelines through CI/CD
  • Experience with Graph Neural Networks (GNNs) for analyzing user similarity and clustering
  • Familiarity with deployment of real-time analytics tools and dashboarding, such as Looker, Tableau, or Snowflake

We Offer

  • Remote work options
  • Opportunity to work with cutting-edge technologies
  • Collaborative and innovative work environment

About the Company

EPAM Systems is a global software engineering and product development company that partners with many of the world’s leading businesses to deliver digital transformation and technology innovation.

© EPAM. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

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