Software Engineer - Platform & Infrastructure

| San Francisco
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At Sisu, we're building a software platform that empowers people to make better decisions using data. Based on years of cutting-edge research at Stanford, Sisu enables users to quickly and comprehensively understand what’s driving their key metrics, so they never miss a window of opportunity to act.


Sisu is a fundamental rearchitecture of how users interact with data. Instead of relying on users to tell us what they want to see, as in traditional dashboarding systems, Sisu predicts users’ intent based on their metrics of interest, and past behaviors. We take this kind of predictive analysis for granted in consumer applications (e.g., Netflix, Google, Facebook), but the hardest interface design and ranking problems lie in making private data found in everyday organizations actionable. The key problem we’re solving as a first step in this direction is to help identify what’s driving change in key metrics like revenue, retention, and churn among the enormous set of factors like user demographics, campaigns, and acquisition channels. To do so, we combine statistical analysis and machine learning at scale to provide users personalized, real-time diagnoses of changes in their metrics via an explainable, interpretable user interface.


As a Software Engineer, you’ll have the opportunity to shape the future of the Sisu Engine - a query processor that is optimized for hypothesis testing at a large scale with speeds of millions of records faster than any other system. You’ll have the opportunity to work on challenging technical problems combining data management, machine learning, distributed systems and develop key features that can be attributed to only a handful of engineers.

Responsibilities

  • Design, engineer, and operate Sisu's scalable parallel data processing engine, including distributed query processing, columnar execution, and streaming updates
  • Develop novel and scalable systems combining hardware-accelerated data processing with machine learning and statistical hypothesis testing
  • Technical leadership
  • Shape the engineering culture through mentorship
  • Build out our data plane 
  • Implement new analyses in our performance-critical data processing engine
  • Optimize and scale data ingest and workload distribution
  • Actively participate in customer POCs to optimize customer experience and adoption.
  • Work collaboratively with multiple departments such as Sales, Marketing, and G&A.

Preferred Qualifications

  • Fluency with a manual memory-managed language (C++, C, etc.) OR Rust
  • Background in database internals or building core components for data processing systems (query compilation, query execution, storage engines, transaction processing)
  • Strong CS fundamentals including data structures, algorithms, and distributed systems.
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Location

575 Mission St., Suite 3200, San Francisco, CA 94105

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