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Database Systems Expert - PhD

Role overview

Qualifications

  • 5+ years of hands-on database-engine internals experience or a database-systems PhD
  • Deep experience with storage engines, query execution, optimization, transactions, replication, or related low-latency systems
  • Strong implementation skills and clear explanations of correctness and performance tradeoffs

Responsibilities

  • Design challenging, self-contained database engineering tasks
  • Build checks for correctness, failure handling, concurrency, retries, and regressions
  • Evaluate performance measures such as latency, throughput, and memory use
  • Write clear grading criteria for engineering judgment

Key facts

Hard skills

Other skills

  • Collaboration

About the company

Mercor logo

Mercor

  • Job Boards & Talent Marketplaces
  • 51–200
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

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Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Database Systems Evaluation Expert
Type: Contract
Compensation: $2200 per task
Location: Remote

Role Responsibilities

  • Design challenging, self-contained database engineering tasks.
  • Build checks for correctness, failure handling, concurrency, retries, and regressions.
  • Evaluate performance measures such as latency, throughput, and memory use.
  • Write clear grading criteria for engineering judgment.
  • Collaborate with technical reviewers to refine and validate tasks.

Qualifications

Must-Have

  • 5+ years of hands-on database-engine internals experience or a database-systems PhD.
  • Deep experience with storage engines, query execution, optimization, transactions, replication, or related low-latency systems.
  • Strong implementation skills and clear explanations of correctness and performance tradeoffs.

Application Process (Takes 20–30 mins to complete)

  • Complete a self-paced technical assessment with recorded verbal responses and a coding exercise.
  • Use a laptop or desktop with a camera, microphone, and entire-screen sharing.
  • Have your own editor and terminal ready, along with Python 3.8+ and a compiler for C, C++, Rust, Go, or Java.
  • The assessment includes a starter kit and public tests.
  • Complete the assessment independently, without outside AI assistance.

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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