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We make logic analyzers, debugging tools for electrical engineers and embedded programmers. It's also a pretty popular reverse engineering tool. If you like playing with Arduinos & electronics, you might have heard of us.
Check out the hiring video on our site, www.saleae.com/jobs. Shoot us an email to email@example.com!
I love talking about what we do so if you're curious at all, feel free to write in!
Oh, and if you don't have a hardware/EE background, don't sweat! Although that helps, there is no need to have any electronics background at all.
We're a fast-growing startup working on cutting-edge email + cloud solutions. Some of the things we do:
- Run one of the largest email migration platform in the world
- Built our own programmable distributed SMTP stack from scratch
- Classify the type of email platform used by millions of domains
If you are interested in enterprise software, large-scale processing, email protocols, performance optimization and distributed systems, we want to hear from you. We're fully profitable with unmatched opportunities to make a big impact, ship code often and make a lasting contribution to a promising startup.
You will be working closely with our biological engineers to write the code that provides the backbone for our synthetic biology pipeline. Work may include programming to control robotic DNA construction, automate measurement processes, design genes and genomes, or manage our process workflow for building organisms. It will depend what's most important once you start - this is a fast moving field and we're a young company. You don't need previous biology experience: Ginkgo is a great environment for amazing programmers to learn to hack biology.
Ginkgo's programming languages of choice are Ruby, Python, C, or DNA, but you must be someone who loves writing elegant code in any language. Most importantly, you should be passionate about engineering biology. Applicants must be able to start within 6 months.
To apply, visit https://ginkgo.resumetracker.com/public/job_detail/83
Plaid makes it simple for any developer or application to link with credit and debit card spending data. In the process, we're generating one of the largest transactional data sets in the world, and using machine learning and statistical analysis to draw insights about how consumers spend their time, money, and attention.
We're a small, all engineering team - looking to bring on more ambitious, fun team members. Our stack is made up of Node, Hadoop and Hive with Mongo and Redis. We're looking for experienced generalists, and prefer fast learners to specific experience with our stack. Whether you're a mobile developer, data scientist, or or a resident philosopher we'd love to hear from you.
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