machine learning engineer

EPAM Systems provides software development, IT services, and IT consulting to a global client base through a diverse team of professionals located in over 55 countries.

• 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.

• 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;
• English 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.

• Work on a flexible schedule remotely or from any comfortable offices or coworking spaces in Ukraine;
• Receive the necessary equipment to perform work tasks;
• Change projects and technology stacks within EPAM;
• Gain experience in various business domains;
• Relocation opportunities may be available for eligible candidates, depending on the role and openings at other EPAM locations;
• Participate in volunteer, charity programs and communities;
• Plan individual career path and receive regular feedback;
• Improve English for free with certified teachers;
• Undergo free training and certification in AWS, GCP, or Azure Clouds;
• Access internal E-learn training program and corporate accounts on LinkedIn Learning and Get Abstract;
• Study at EPAM Solution Architecture School and develop as a leader through specialized programs;
• Vacation and sick leave, including sick leave without a medical certificate;
• Voluntary Medical Insurance programs including medical treatment and preventive options;
• Medical insurance for family members at corporate rates;
• Company support during significant life events;
• Support for psychological comfort with discounts on services from mental health specialists or coaches;
• E-kids program for EPAMers' children.