Microsoft Research Intern - SQL Query Processing 

United States, Texas, Austin 

248619201

• Currently enrolled in a PhD program in Computer Science or a related STEM field.

Other Requirements

• Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
• In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.

• Proficient technical background in algorithms (Big-O complexity analysis).
• Experience in writing CPU cache-aware algorithms that maximize performance on a given hardware generation (including structuring code to avoid branch mispredictions).
• Unmanaged language expertise.
• Good understanding of database system internals.
• Working knowledge of x86/x64 assembly.
• Ability to do performance analysis/improvements on multi-threaded server software.
• Experience in building and shipping production grade software or services.
• Results-oriented with a passion for delighting customers with our work.
• Ability to work collaboratively, solve programs in groups, and celebrate success as a team.

Learn more about base pay ranges and pay equity:

Responsibilities Include:

• Design, code, test, and develop features with good quality, maintainability, and end to end ownership.
• Be part of the on-call rotation for maintaining service health.
• Mentor new engineers to bring them up to speed in software development environment.
• Invest in code health/refactoring efforts to improve our ability to execute on shipping software to meet customer needs in a timely manner.
• Design and develop highly-efficient code that scales to allow queries to run efficiently over very large data volumes.