Senior Data Scientist / ML Engineer (Semantic Search)

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).Nice-to-Have Skills Description:- Experience of work in distributed teams, with US customers- Experience with LLMs, RAG pipelines, and vector retrieval frameworks.- Knowledge of Spring Boot, FastAPI, or similar backend frameworks.- Familiarity with Kubernetes, Docker, and cloud platforms (AWS/Azure/GCP).- Experience with MLOps and model monitoring tools.- Contributions to open-source search or ML projects.Languages:English: B2 Upper Intermediate