job specification

Project Description:

The primary goal of the project is the modernization, maintenance and development of an eCommerce platform for a big US-based retail company, serving millions of omnichannel customers each week.

Solutions are delivered by several Product Teams focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart.

Current overriding priorities are new brands onboarding, re-architecture, database migrations, migration of microservices to a unified cloud-native solution without any disruption to business.

Responsibilities:

• We are looking for an experienced Data Engineer with Machine Learning expertise and good understanding of search engines, to work on the following:
• - Design, develop, and optimize semantic and vector-based search solutions leveraging Lucene/Solr and modern embeddings.
• - Apply machine learning, deep learning, and natural language processing techniques to improve search relevance and ranking.
• - Develop scalable data pipelines and APIs for indexing, retrieval, and model inference.
• - Integrate ML models and search capabilities into production systems.
• - Evaluate, fine-tune, and monitor search performance metrics.
• - Collaborate with software engineers, data engineers, and product teams to translate business needs into technical implementations.
• - Stay current with advancements in search technologies, LLMs, and semantic retrieval frameworks.

Mandatory Skills Description:

• 5+ years of experience in Data Science or Machine Learning Engineering, with a focus on Information Retrieval or Semantic Search.
• Strong programming experience in both Java and Python (production-level code, not just prototyping).
• Deep knowledge of Lucene, Apache Solr, or Elasticsearch (indexing, query tuning, analyzers, scoring models).
• Experience with Vector Databases, Embeddings, and Semantic Search techniques.
• Strong understanding of NLP techniques (tokenization, embeddings, transformers, etc.).
• Experience deploying and maintaining ML/search systems in production.
• Solid understanding of software engineering best practices (CI/CD, testing, version control, code review).

Languages:

• English: B2 Upper Intermediate