Naomie Gao

Software Engineer @ MongoDB || Duke CS & Stats

New York, New York, United States

About

Duke University alumna interested in applying technological solutions to create and enhance innovative products. Also interested in applying technology and data-intensive processes to other areas of research, including biology and education. Passionate about exposing students to university and industry-associated experiences.

Experience

  • MongoDB (1 yr 11 mos)
    • Software Engineer 3
      Feb 2026 - Present · 5 mos

    • Software Engineer 2
      Aug 2024 - Feb 2026 · 1 yr 7 mos

  • Undergraduate Teaching Assistant at Duke University
    Aug 2022 - May 2024 · 1 yr 10 mos

    COMPSCI371: Elements of Machine Learning COMPSCI 260: Introduction to Computational Genomics STA199: Introduction to Data Science STA211: Mathematics of Regression COMPSCI216: Everything Data ECON362: Discovering Game Theory Instruct 300+ undergraduates through hosting weekly office hours, grading assignments, and answering forum questions.

  • Software Engineering Intern at MongoDB
    Jun 2023 - Aug 2023 · 3 mos

    Built top 20 customer-demanded feature to export logs to S3 buckets, streamlining process to be more efficient than existing implementation and replacing need for complex manual scripts, reducing dependency on legacy software. Owned end-to-end implementation from conceptualization, collaborating to construct API, UI, and backend components.

  • HackDuke (1 yr 8 mos)
    • Co Director
      Oct 2021 - Dec 2022 · 1 yr 3 mos

      Managed team of 50+ members in organizing the nation's premier hackathon for social good. Organized weekend hackathon with over 300 participants, resulting in over $2,500 of prizes given out.

    • Outreach Director
      May 2021 - Oct 2021 · 6 mos

      Co-directed Outreach team through onboarding new members, creating weekly plans, and keeping team on track of goals.

  • Software Engineering Intern at MongoDB
    Jun 2022 - Aug 2022 · 3 mos

    Developed benchmark dashboards to compare query engines, informing stakeholders in identifying query regressions. Optimized filtering in database queries to accelerate information retrieval pipeline by implementing match expressions. Introduced customer-demanded feature of permitting setting of empty fields in queries through more nuanced parsing logic.