Senior Backend Software Engineer, ReadySet
Cloud Platform
$160-210k
+ Equity
Database scaling platform & SQL query cache
Job no longer available
Database scaling platform & SQL query cache
21-100 employees
Job no longer available
$160-210k
+ Equity
21-100 employees
Company mission
To build a modern database scaling platform that sits in front of existing databases and dramatically improves database performance by accelerating reads.
Role
Who you are
- We’re looking for software engineers who are experts in building systems software with a specialization in Distributed systems, Storage or FileSystems, Database Services, Caching Services or similar services and are excited to continue expanding their depth of knowledge in these fields
- 5+ years of hands-on software engineering experience
- Backend engineering focus
- Experience with Python and AWS a must
- Experience working on Distributed Systems, Database Systems and Cloud based Services
- Experience with service-oriented architectures
- Experience with building Cloud Native solutions on AWS, Azure, and Google Cloud is highly desirable
- Exposure to building a traditional machine learning system or a service that uses public or self-hosted LLM models
- Bachelor's degree in Computer Science, Engineering, or a related field
What the job involves
- In this role, you will scope, design, and build parts of the Cloud platform for the Readyset cache. Experience with building scale-out services is desirable
- In your day-to-day work, you’ll iterate on and build production-level code with a growing user base, robust design structure, and rigorous code quality.
- As a part of a small and growing team, you’ll also work cross-functionally to help scope out product requirements, respond to new customer needs, and develop code to solve complex problems
- As a part of our engineering team, you’ll collaborate with other team members to contribute to process improvements, give product and architectural feedback, and work towards making Readyset more robust and feature-complete
- In this role, you will build a significant portion of the system hands-on while also guiding others to make sound engineering choices in design and code
- The systems you architect and build will be robust, scalable, supportable, and manageable
- You will use your speech and written communication proficiency to influence others and establish engineering processes and guidelines
- Additionally, you will interact with leaders and colleagues across the company and work collaboratively on projects
- As a thought leader in the domain, you will blog about and evangelize the amazing engineering systems you and your colleagues are building
Our take
Once applications begin to gain popularity, databases need to be able to handle an increased volume of requests, larger data sets, and more complicated queries. Databases that can’t keep up can lead to substantial business losses precisely when there’s most to be gained: Super Bowl weekend, for example, or Black Friday. ReadySet is looking to help companies dodge this issue.
The company has developed a plug-and-play data caching layer that pre-computes and caches query results in relational databases, meaning that database reads can remain fast. In fact, ReadySet claims that the layer supports millions of reads per second “with sub-millisecond latencies on a single node”.
This is a hugely impressive feat from the company, founded by a team of data systems researchers from MIT, for whom ReadySet began as Noria - the open source streaming data-flow system developed in the lab. Plus, surveys suggest that there’s substantial enterprise appetite for this kind of product. This is partly thanks to unfit legacy systems, and partly in anticipation of the swelling user and data volumes anticipated for the years ahead - both are good news for ReadySet.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Apr 2022
$29m
SERIES A
Total funding: $29m
Leadership
Alana Marzoev
(Founder & Chairman)Previously worked on ML engineering at BioBots, then ML and Computer Systems Research first at UC Berkeley College of Engineering's RISELab, then at Cornell University College of Engineering. Subsequently worked in cloud infrastructure at Microsoft, and recently completed an MIT PhD in distributed systems and databases.
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