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We encourage you to first learn more about our company by reading the remainder of this webpage, which describes the motivations for our work, job openings, and expectations.
Alternatively, if for some reason you are too old-fashioned to use an electronic form, you can e-mail your curriculum vitae, github link, and a few paragraphs about yourself and why you want to work with us to: email@example.com
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QED aims to offer unique opportunities to talented coders, scientists, makers, and artists that wish to work alongside us in building technologies to positively affect the world. After working for almost a decade on a diverse mixture of industrial jobs, we are trying our best to select projects carefully, so that staff can concentrate on interesting problems for which there is little doubt that the solutions will benefit, and clearly not harm, the welfare of others.
Our current focus is human health and agriculture in developing countries. We believe that these topics lie at the crux of many core challenges facing humanity, such as rural poverty and high mortality rates in developing countries, epidemics of nutrient deficiency and disease, and conflict over scarce natural resources. The general optimization problem is to balance the ballooning long-term needs of our population against our planet’s limited capacities in the most sustainable way possible. These problems are quantitatively described by The Sustainable Goals, of which we focus on goals 2, 3, and 15. Our contributions may be small, but if we can bring more awareness to clever applications of technology to this area, perhaps the network effects over time can be large. We believe this kind of work is more meaningful for technologists than advertising, social media, Wall Street, or military weapons … even if the market says otherwise.
To expound on why technologists are needed in this area, agriculture and health in developing countries are big data problems requiring modeling of complex natural processes with untold degrees of freedom. However, these fields is wholly unprepared for the application of modern machine learning, irrespective of what advertisements may claim. Despite its importance, agriculture lags far behind many fields in terms of both the quantity and quality of data being collected, particularly in regions such as Sub-Saharan Africa or Southeast Asia. The challenges of collecting agricultural data are manifold, and include limited access to finance, poor infrastructure, and the logistics of coordinating large-scale ground operations. Furthermore, even when data is collected, it is often not stored in a manner that easily lends itself to analysis or web/mobile application development. As a whole, the agricultural field is decades behind in terms of data science practices and standards of rigor, in which conclusions are regularly being drawn based on analyses carried out in Excel on kilobyte-sized datasets.
Software and hardware engineering can play major roles in advancing the envelope of what is possible with development projects, by enabling scalable data collection, performant data management, modern data mining, and worldwide data dissemination. This is where QED can provide assistance, reaching out to clients in the most need of technological help, often working in third-world environments where this help is least readily available.
Most of our work is related to software engineering as our core competency. However, we are also looking for application analysts with excellent communications skills, hardware engineers with background in optics, and exceptionally strong data scientists that are well trained in both traditional and algorithmic data modeling.
Below we list our Basic Requirements which should be satisfied by all staff. Afterwards, we describe our Core Application Verticals, Core Technical Verticals, [current] Core Programming Languages, and [current] Core Frameworks and Tools in use. We then list our current job openings which reference these sections.
Possession or pursuit of a degree in computer science or hardware engineering, or comparable professional experience.
Dedication of at least 20 hrs/week.
Good fluency in English speaking and writing (typing > 35 wpm).
Basics of efficient algorithms.
Willingness to participate in regular code reviews, git commits, and working in teams.
Development only on UNIX-based or OSX-Darwin platforms.
A few remarks on our culture. The term “too big to fail” has been used to justify bailouts for large corporations. We propose an alternative mantra: “too big to succeed”. At a large corporation, responsibilities are often obfuscated or diminished by the fact that most staff are small cogs in a machine consisting of +50,000 cogs. High levels of bureaucracy, minuscule project ownership, and constant meddling from business agents make innovation very difficult.
The second contrarian mantra we propose is, “too small to fail”. While the paths that smaller companies take may be unconventional, they are also (1) more able to learn quickly through rapid experimentation, unfettered by excessive internal regulations, and (2) highly motivated to work cleverly and succeed, as no one is there to bail them out and inefficiencies cannot be sustained. Consequently, based on interviews to date we have found that our standards are at least comparable if not higher than that of most blue chip tech companies.
For these reasons, we impose an extremely light amount of bureaucracy. There is no matrix organizational structure. We do not focus on careerism and politicking, and encourage focusing only on the mission and delivering excellent work for clientele, by any means necessary. Regardless of one’s age or position in life, we ask that our staff make serious commitments if they choose to work with us, which will be reciprocated by equal devotion to the cause from others.
In closing, we seek people eager for a challenge in taking on greater levels of responsibility, who are truly passionate about their craft as not just something they do for work but also for fun, and are genuinely interested in the humanitarian verticals that we work. If this sounds like you, we would really like to learn more about you.