Research Engineer - Distributed System Performance Modeling, Analysis & Optimization

San Diego, CA, United States

Job Title: Research Engineer - Distributed System Performance Modeling, Analysis and Optimization at TigerGraph (View all jobs) San Diego, California TigerGraph is the world’s fastest graph analytics platform designed to unleash the power of interconnected data for deeper insights and better outcomes. We welcome people from all backgrounds who seek the opportunity to help build the next generation graph computing and analytics platform. TigerGraph is looking for a Research Engineer in the Innovation Lab to conduct advanced research and development in the area of performance modeling, analytics and optimization for large-scale distributed systems with hundreds and thousands of servers. The ideal candidate should be an experienced performance modeler / engineer versed in state-of-art research and tools in large scale distributed systems performance modeling, creative innovator with the curiosity and desire to go beyond what has been done before, as well as proven ability to apply advanced analysis into accurate models that can predict system performance, identify bottlenecks and propose optimizations. Great insights to TigerGraph and the Graph Space: https://info.tigergraph.com/hubfs/Collateral/TigerGraph-Rise-Future-Graph-WP.pdf Recent press release about TigerGraph Cloud: https://siliconangle.com/2018/11/27/tigergraph-brings-graph-database-cloud/ TigerGraph completes $105 million series C Funding News: https://techcrunch.com/2021/02/17/tigergraph-raises-105m-series-c-for-its-enterprise-graph-database/ Responsibilities Research, design and prototype innovative approaches to model large-scale parallel graph database performance Validate and fine-tune performance model via performance test results from running systems Analyze performance models and identify bottlenecks for optimization Research performance optimization algorithms and validate by the performance model Work with product engineering to turn performance optimization algorithms into production implementation Collaborate with external researchers and partners closely to jointly develop new innovative approaches on large scale distributed system performance modeling Author, publish and present innovative ideas in internal and external conferences and online media. Requirements Master’s or PhD in Computer Science, Maths, Engineering, or a related field. In-depth knowledge on large-scale distributed systems, familiar with state-of-art research and tooling in the field. 5+ years of hands-on experience in performance analysis and optimization of large-scale distributed systems, distributed database engine experience is preferred. Passion to take on hard and complex problems to have an impact on practical enterprise applications. 'Can do' attitude with a strategic and rigorous mindset and be comfortable working in a fast paced, multi-faceted environment. Demonstrated collaboration skills with peers inside and outside companies. Strong communication skills with both technical and non-technical audiences.

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