As we roll into the peak of internship season, it seems like a worthwhile time to talk about just what it is that interns do in their time at Palantir: our software engineering interns are full members of the development team from the day they arrive. During their time with us, they design, implement, and test their projects while alongside the full time engineers.
We believe in hitting the ground running; in fact, before you get your badge on the first day, you must commit code. But don’t worry, this all takes place under the watchful eyes of your mentor: a full-time engineer who’s there to guide through everything from our development environment, how to write specifications, to software architecture, to how to figure out which cafe has the best lunch.
You can broadly break down the projects the Palantir interns worked on into a number of categories:
- User Interface/Experience & Visualizations – extending and refining the GUI tools used to access and analyze data.
- Data Server Infrastructure – adding capabalitites and scalability to our core big data analytic offerings.
- Testing & Performance Measurements – building the automation frameworks that allow us to do extensive testing and performance measurements.
- New Platform Features – creating new interfaces, APIs into our platforms.
- Geospatial Enhancements – adding in new geospatial features at various levels of our software stack.
Join Us In 2012!
We’re currently hiring for our 2012 intern class as well as full time positions. For those interested in working on the sorts of projects mentioned here, you’ll want to apply for this job:
For other internships, check out our open positions page.
From those from non-traditional schools that have co-op programs that run during the year, we offer those as well. Go ahead and apply for the appropriate intern position and make a note of when you’d like your co-op to be in your application.
Read on to dive into a large sampling of software engineering projects our interns worked on this past summer.
- Microsoft Kinect integration for Palantir, including new user interfaces and interactions – (Quentin and Ben, Oxford)
- Visual SearchAround, an intuitive interface that allows users to define complex search queries to be performed on the graph – (Jordan, Stanford)
- Hierarchy Helper for intuitively displaying and laying out graph nodes in an organizational chart – (David, Stanford)
- Ability to export Palantir graph as an interactive HTML5 application – (David, MIT)
- Frontend for importing data via webapi – (Mihail, Caltech)
- Import and reindex of Palantir’s massive-scale distributed data store, Phoenix, using Hadoop tasks – (Dylan, Berkeley)
- Distributed media store to improve scalability and performance of core Palantir – (Katherine, MIT)
- Cassandra data store that contains data imported via webapi – (Moses, Columbia)
- Pipelined computation and smart-salvaging caching for a data-intensive application – (Mingyu, Stanford)
- Application for creating automated tests within the UI – (Anuraag, CMU)
- Measuring and recording platform performance using AspectJ – (Tyler, Berkeley)
- Testing for Palantir Mobile for Android, including planning the feature, testing the feature in development, and creating a testing infrastructure for feature stability going forward – (Zach, Bowdoin)
- Libraries and tools for automation tests using Robotium, an Android automation framework, and stress tests including 50 Android emulators – (Ethan, CMU)
- In house automation framework expansion for testing Search Around, including harnesses to represent all UI components and their interactions – (Billy, CMU)
- Naïve Bayes text classification of properties identified by users on documents in Palantir – (Andrew, CMU)
- Intelligent parser for arbitrarily-formatted time-series for improving data import usability – (Andy, Stanford)
- Palantir REST API expansion, including new endpoints that enabled users to read and process documents from a user-friendly webapp – (Jonah, Stanford)
- Graph flows with several orders of magnitude more backing data and new user interactions – (Blake, Stanford)
- Collaboration within the Palantir platform, enabling data sharing within small teams and rich messages sent directly to other users – (Caitlin, Stanford)
- Graph sharing between Palantir deployments – (Justin, UIUC)
- Query language for Palantir that enables 1-click workflows for complex, multi-step searches – (Huw, Oxford)
- Map application for plotting geospatial data – (Yanping, MIT)
- Faster, horizontally scalable geospatial search service – (Jack, UIUC)
- Map elevation helper, enabling users to see elevation profiles of terrain and add line of sight to their mission risk analysis – (David, Cornell)
- Added geosearch support to Palantir’s massive-scale distributed data store, Phoenix – (Bobby, Stanford)