Staff Software Engineer - ElasticSearch (4-10 yrs)

Role Overview :

As a Staff Software Engineer specializing in Search and Recommendations, you will play a critical role in designing, developing, and scaling our search infrastructure. You will collaborate with cross-functional teams to enhance product discovery and improve customer experience using ElasticSearch, machine learning, and personalization algorithms. You'll be working on optimizing search relevance, implementing state-of-the-art recommendation models, and ensuring the system is scalable, fast, and highly available.

Key Responsibilities :

- Search Optimization : Design, develop, and optimize search algorithms using ElasticSearch, focusing on relevance, performance, and multi-language support.

- Recommendation Systems : Develop and enhance recommendation algorithms using collaborative filtering, content-based filtering, and hybrid approaches. Implement realtime, personalized product recommendations that drive engagement and sales.

- Scalable Architecture : Design scalable search and recommendation systems capable of handling millions of queries daily with a focus on high availability, low-latency, and resiliency.

- Data-Driven Decisions : Work closely with data science / analytics teams to leverage machine learning models, vector databases, and user behavior analytics to improve product ranking, personalization, and search relevance.

- Cloud Infrastructure : Implement and optimize search and recommendation infrastructure on AWS, GCP, or other cloud platforms. Ensure the system scales to meet traffic demands, optimize performance, and maintain high uptime.

- Multilingual Search : Lead efforts to enhance search functionality across multiple languages and regions, ensuring accurate, localized, and context-aware results.

- Innovation : Stay updated with the latest advancements in ElasticSearch, LLMs (Large Language Models), vector search, and recommendation algorithms. Apply these innovations to continuously improve the platform.

Required Skills & Experience :

- 3+ years of experience in software engineering, with a focus on search technologies, recommendation systems, or personalization.

- Proven expertise in ElasticSearch, including tuning relevance models, query performance optimization, and large-scale search infrastructure.

- Experience in Recommendations : Hands-on experience with recommendation algorithms such as collaborative filtering, content-based filtering, and hybrid models.

- Machine Learning Knowledge : Proficiency in machine learning techniques for search relevance, personalization, and user behavior modeling.

- Experience with Vector Search : Experience with vector-based databases (e.g., Pinecone, Milvus) for improving search through semantic understanding and natural language processing (NLP).

- Cloud Infrastructure Expertise : Solid understanding of cloud-based architectures on AWS, GCP, or other cloud platforms with experience in building and scaling distributed systems.

- Multilingual Search Experience : Proven ability to handle and optimize multilingual search results, including localization and handling cross-language queries.

- Strong programming skills in Python, Java, or Scala for building high-performance, realtime systems.

- Experience in Personalization : Experience integrating machine learning-driven personalization systems that improve user engagement.

- Excellent problem-solving skills and ability to deliver high-quality code in a fast-paced environment.

- Strong communication skills and ability to collaborate with cross-functional teams.