Data Engineer

Full-time

Hybrid

Deadline

October 14, 2024

About the organization

HAI Stanford Logo

Stanford Institute for Human-Centered Artificial Intelligence

Organization type

Academic Institution

In A Nutshell

Location

Hybrid Stanford, California, USA

Salary

$96,000-$140,000

Job Type

Full-time

Experience Level

Mid-level

Visa Sponsorship

Not Available

Deadline to apply

October 14, 2024

Design and implement data models that support specific analytic needs. This includes providing leadership in the areas of data modeling techniques that consider standards and best practices.

Responsibilities

  • Design and implement databases and data pipelines to support the lab’s research needs.
  • Develop and maintain machine learning models, including natural language processing models.
  • Train other researchers in data management, GCP, machine learning, and NLP techniques.
  • Conduct code review and ensure the quality of code developed by the lab members and research assistants.
  • Work collaboratively with researchers and other members of the lab to ensure the timely completion of projects.
  • Stay up-to-date with the latest developments in big data engineering and machine learning.
  • Ensure efficient use of Cloud Credits across projects.
  • Identify and assess potential data acquisitions.
  • Contribute to technical discussions at a big picture level and provide feedback on decisions and interpretations.

Skillset

  • PhD, Master’s degree, or Bachelor’s degree in Computer Science, Software Engineering, or a related field.
  • 5+ years of experience in software development and big data engineering.
  • Strong programming skills in Python and experience with relational databases.
  • Experience in developing and deploying machine learning models, particularly in NLP.
  • Experience with cloud computing platforms (e.g. GCP, Azure, or AWS).
  • Familiarity with distributed computing frameworks (e.g. Hadoop, Spark).
  • Good communication and collaboration skills.
  • Ability to work independently and manage multiple projects simultaneously.

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