Data Infrastructure Developer
Requisition # 2017-7183
Department Princeton Neuroscience Inst
Category Information Technology
Date Posted 4/12/2017
Full-Time / Part-Time Full-Time
Application Deadline ..
The Seung Lab at Princeton University specializes in reconstructing the connections between neurons by analyzing electron microscopic brain images. The lab has received major funding from IARPA to reconstruct the connectome of a cubic millimeter of neocortex. This presents new engineering challenges as the volume is 1000x larger than existing reconstructions. This amounts to a petabyte of image data that must be stored and processed through our artificial intelligence (AI) pipeline and reviewed by human effort.
The lab is looking for an Infrastructure Developer experienced in large scale data storage and data processing systems to help scale the lab's existing pipeline for this petabyte challenge. This is a one year term position with the possibility of renewal based on performance and continued funding.
For more information, see
Please submit your application online and also email your CV and a longish C++ code sample directly to Prof. Sebastian Seung email@example.com
- Scale machine learning algorithms and data access requirements
- Architect storage and application backend systems
- Develop and establish API's for new backend systems
- Migrate remaining data infrastructure to the cloud
- Bachelor's degree in Computer Science or a related field; or equivalent education/experience
- Master level knowledge of at least one core programming language such as C++, Java, Python
- Expert level knowledge of at least 2 other programming languages.
- Designed and deployed database solutions and large scale applications
- Excellent proficiency in architecting large scale data processing pipelines
- In-Depth knowledge of server administration / cloud orchestration
- Strong Computer Science fundamentals such as algorithms and data structures
- Strong desire to learn new technologies
- Articulate and strong communication skills
- Machine Learning / Deep Learning
- Both AWS and Google Cloud
- Front end development experience
- Continuous Deployment / integration
The final candidate will be required to complete a background check successfully.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW
Standard Weekly Hours
Eligible for Overtime
Essential Services Personnel (see policy for detail)
Estimated Appointment End Date
Comments Related to End Date
1 year term position with possibility of renewal based on satisfactory performance and continued funding.
Physical Capacity Exam Required
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