Lead Machine Learning Engineer (Personalization & AI Models)

About the role

We are looking for a Lead Machine Learning Engineer to drive the design, development, and optimization of user segmentation, recommendation, and embedding models for a large‑scale mobile app personalization system. The role focuses on multi‑vector representations, real‑time inference, and integration with modern data and AI platforms.

Key responsibilities

• Develop and fine‑tune embedding models using sentence‑transformer architectures for user profiling.
• Implement KNN‑based recommendation pipelines that score and rank content in real time.
• Leverage AWS Personalize SDK to train, deploy, and continuously adapt models to evolving user behavior.
• Integrate embedding models with Databricks, RudderStack, and other AWS services to keep user profiles up to date.
• Optimize PGVector and Redis for fast vector lookups and caching.
• Collaborate with data engineers to build robust ML pipelines for training, validation, and deployment.

Required profile

• Strong background in machine learning, deep learning, and AI‑driven personalization.
• Proven experience delivering production‑grade recommendation or similarity systems.
• Ability to work in an event‑driven, real‑time feature‑engineering environment.
• Fluent English communication (B2+ level).

Required skills

• Python
• PyTorch
• TensorFlow
• AWS Personalize SDK
• Amazon SageMaker
• Databricks
• Delta Lake
• Apache Spark
• PGVector
• Redis
• K‑Nearest Neighbors (KNN)
• Sentence‑transformer models

What we offer

• Remote work from anywhere in Ukraine.
• Flexible schedule and modern coworking spaces.
• Access to diverse projects across insurance, e‑commerce, healthcare, finance, media, and AI.
• Opportunities for career growth, mentorship, and cross‑domain experience.
• Equipment provision and possible relocation within EPAM network.