ElasticSearch Architect

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About the role

As an Elasticsearch Architect/Expert, you will be the core member of the company's Elasticsearch ecosystem. You will not only ensure the stability, performance, and security of our ultra-large-scale clusters but, more critically, lead the adoption of Elasticsearch's latest AI features (such as vector search and machine learning) to build advanced intelligent applications. These include next-generation semantic search systems, intelligent Q&A chatbots, anomaly detection platforms, and LLM-enhanced solutions. You will take full ownership from architecture design and technology selection to implementation, empowering the company's business with robust AI capabilities. If you enjoy and ready to pick up these challenges, then you will be one that we are looking for.

What you will do

Architecture Design and Strategy

·       Design, plan, and implement company-wide, highly available, and scalable Elasticsearch cluster architectures to meet petabyte-scale data storage and millisecond-level retrieval requirements.

·       Lead the integration and convergence of Elasticsearch with the AI/ML technology stack (e.g., vector database concepts, LLM frameworks), defining the long-term technical roadmap.

·       Evaluate and introduce new features and AI-related functionalities of the Elastic Stack (ELK), driving technological upgrades and iterations.

AI and Intelligent Search Development:

·       Master and apply Elasticsearch's AI capabilities, including but not limited to:

·       Designing and implementing vector search systems to build semantic similarity matching and hybrid search (keyword + vector) based on embeddings.

·       Utilizing Elasticsearch's ML module or external ML module for anomaly detection, log classification, and business metric forecasting.

·       Developing and optimizing Retrieval-Augmented Generation (RAG) pipelines, using Elasticsearch as an external knowledge base to enhance the capabilities and accuracy of large language models.

·       Deploying and managing Elasticsearch Learning to Rank models to improve the intelligent ranking of search results.

·       Collaborate with data scientists and algorithm engineers to seamlessly deploy and run machine learning models in Elasticsearch production environments

Performance Optimization and Operations:

·       Conduct in-depth performance tuning for complex search queries and write operations, addressing performance challenges especially in high-dimensional vector search scenarios.

·       Establish comprehensive cluster monitoring, alerting, and disaster recovery systems to ensure 24/7 high availability.

·       Troubleshoot and resolve various complex issues within the cluster, performing root cause analysis

What you will need

·       B.S or above in Computer Science or related field

·       Minimum 5 years of hands-on Elasticsearch experience with a deep understanding of its core principles (inverted index, text analysis, sharding, routing, etc.).

·       Proven success in designing, deploying, and operating clusters from scratch with at least 10 nodes and petabyte-scale data.

·       Proficiency in Elasticsearch index design, mapping optimization, DSL query writing, and performance tuning.

·       Must have: Extensive practical experience with vector search, familiar with embedding models, vector index principles, and performance optimization.

·       Must have: Hands-on experience building and optimizing RAG systems, understanding how to leverage Elasticsearch to enhance LLMs.

·       Familiarity with Elasticsearch's built-in machine learning features (anomaly detection, data frame analysis, etc.) and experience applying them in production environments.

·       Understanding of how to integrate Elasticsearch with external ML workflows (e.g., PyTorch, TensorFlow, Scikit-learn).

·       Proficiency in Java or Python for relevant SDK development and scripting.

·       Familiarity with the entire ELK stack, including Logstash for data ingestion and Kibana for visualization and dashboard development.

·       Project experience successfully integrating Elasticsearch with mainstream large language models (e.g., GPT series, LLaMA, ChatGLM) is preferred.

·       Strong both written and oral English is a MUST, Chinese speaking is preferred

About the team

This position will be reported to Big Data Team. Big Data Team is a team operating under IT D&I department. This team is accountable for IT operations in Big Data platform across all sites in Nexperia. Besides that, this team collaborates with business and other D&I teams for the delivery of BI reports, Analytic tools, AI tools and Data Models etc.

Talent acquisition based on Nexperia vacancies is not appreciated. Nexperia job adverts are Nexperia copyright © material and the word Nexperia® is a registered trademark.

D&I Statement

As an equal-opportunity employer, Nexperia values diversity not just because it is the right thing to do but because diverse teams perform better. We are dedicated to being inclusive, and a proof point of this dedication is that we were the main partner of the very first Dutch Paralympic Team NL House during the Paris 2024 Paralympic Games. Our recruitment process is inclusive and accessible to all, and we consider all applicants fairly, as well as providing a safe work environment and reasonable adjustments where requested.

In addition, we offer our colleagues the possibility to join employee resource groups such as the Pride Network Group or global and local Women's groups. Nexperia is committed to increasing women in management positions to 30% by 2030.