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Senior Search Engineer

Slikk

Bangalore, Karnataka, IndiaJobPosted 2mo agoStill listed 3 days ago

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At a glance

Compensation
No compensation found
Location
Bangalore, Karnataka, India
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

The Senior Search Engineer will own and evolve the end‑to‑end search platform, building real‑time indexing pipelines, designing ML‑powered ranking and personalization algorithms, and enhancing discovery experiences while driving experimentation and performance optimization for e‑commerce commerce.

Skills & qualifications

RequiredNice to have

Skills

Apache KafkaIndexingPythonMachine LearningRankingExperimentationNatural Language ProcessingClassification AlgorithmsCDCFeature ExtractionElasticSearchXgboostE-CommercePerformance TuningInformation RetrievalElasticsearch OpenSearchIndex DesignCustom AnalyzersQuery DSLMachine Learning RankingLightgbmFeature EngineeringFaissHnswTokenisationEntity ExtractionIntent ClassificationKafkaReal-Time IndexingAb Testing Frameworks

Qualifications

Bachelor's or Master's Degree in Computer Science Engineering or Related Field5-7 Years Experience Building Production-Grade Search Information Retrieval Systems

Full job description

Responsibilities:

  • Search Infrastructure Ownership: Own the search platform end-to-end, including: Indexing and data modelling, Query understanding and interpretation, Retrieval mechanisms, ML-powered ranking systems, Result serving infrastructure.
  • Real-Time Indexing and Data Pipelines: Develop and maintain real-time indexing pipelines to synchronise: Inventory updates, Pricing changes, Product catalogue modifications from dark stores. Ensure search indices remain fresh and accurate to support quick-commerce operations.
  • Ranking and Personalisation: Design and optimise ranking algorithms that incorporate: Product relevance, User personalisation signals, Inventory availability, Business and merchandising rules. Continuously improve ranking quality to maximise engagement and conversion.
  • Discovery Experience: Build and enhance discovery capabilities beyond traditional search, including Personalized feeds, Category ranking systems, Similar product recommendations, and "Complete the Look" experiences
  • Experimentation and Performance Optimisation: Implement A/B testing frameworks to evaluate and improve search experiences. Define, monitor, and optimise key search quality metrics, including MRR (Mean Reciprocal Rank), NDCG (Normalised Discounted Cumulative Gain), CTR (Click-Through Rate), and Conversion Rate. Optimise systems to maintain P95 latency below 200 milliseconds.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 5-7 years of experience building production-grade Search/Information Retrieval (IR) systems, preferably in e-commerce environments.
  • Strong expertise in Elasticsearch/OpenSearch, including: Index design, Custom analyzers, Query DSL, and Performance tuning and optimisation.
  • Hands-on experience with Machine Learning ranking techniques, such as Learning-to-Rank (LTR), XGBoost, LightGBM, and feature engineering.
  • Experience with embedding-based retrieval systems, including: FAISS and HNSW.
  • Strong programming proficiency in Python.
  • Solid understanding of Natural Language Processing (NLP) concepts for query understanding, including: Tokenisation, Entity extraction, and Intent classification.
  • Experience working with real-time indexing technologies, such as Kafka and CDC (Change Data Capture).
  • Familiarity with search quality experimentation and evaluation frameworks.

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