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Tier-1 brand, Bangalore metro, mid-level generalist title, and unspecified experience increase competition.
Search, IR, and MLOps specialization reduces cross-industry transferability; domain expertise is valued.
Mandatory tech stack (Kotlin, Micronaut, Solr/Elasticsearch, Kafka) increases filtering despite no explicit years.
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Build and evolve large-scale search and discovery systems for Target's digital platforms including information retrieval, query understanding, relevance ranking, semantic search, and machine learning.
Collaborate with product managers, data scientists, machine learning engineers, and other engineering teams to improve search quality and develop scalable, reliable, and performant services.
Design software architecture and influence implementation by proposing designs, providing feedback, and solving operational issues to improve system stability and eliminate recurring problems.
Proficiency in Kotlin and Micronaut for software development.
Experience with search engines such as SOLR and Elastic Search is mandatory.
Experience with streaming systems like Kafka; knowledge of Kafka Streams is an advantage but not mandatory.
Work Experience Required: Prior experience on search technologies is required; exact years not explicitly mentioned in the JD.
Strong software engineering fundamentals combined with expertise in search relevance, ranking, and large-scale distributed systems.
Ability to integrate data science, data engineering, and MLOps concepts into search system development.
Experience designing and implementing scalable, robust systems with data-driven decision making and proactive operational problem solving.