Logo of Huzzle

Internship

• Starts Jul 2

Data Science/Generative AI Intern

Logo of Zeta Global

Zeta Global

17d ago

🚀 Off-cycle Internship

San Francisco

AI generated summary

  • You need a strong background in computer science/physics, experience with generative AI applications, shared-code Python experience, great communication skills, and ideally industry experience. PhD/Master's students near graduation preferred for potential full-time role.
  • You will develop software features, collaborate with team members, experiment with algorithms, collect and organize data sets, and document the development process.

Off-cycle Internship

DataSan Francisco

Description

  • The Generative AI pod within Zeta Global oversees the development of a patented state-of-the-art marketing assistant, ZOE. ZOE is a multi-agent Large Language Model application with advanced architecture and ground-breaking capabilities. You will join a team of industry-leading Researchers and Machine Learning engineers to help with day-to-day R&D work. You will write production-grade code that will be added to the ZOE codebase. You may get a chance to co-author a Generative AI patent.

Requirements

  • Computer Science/Engineering/Physics background with hands-on experience with development of Generative AI applications (OpenAI API, AWS Bedrock, open source LLMs).
  • At least two years of industry/academic experience using python in a shared-code environment
  • Excellent communication skills
  • Prior software industry experience is a major advantage
  • Strong preference for Master’s/PhD students towards the end of the Master’s/PhD degree, with a potential to join as Full Time Employees after graduation

Education requirements

Currently Studying
Masters
PhD

Area of Responsibilities

Data

Responsibilities

  • Develop new software features as part of an industry-leading team
  • Collaborate with other Generative AI team members. Participate in team meetings and brainstorming sessions.
  • Experimentation and testing. Conduct experiments to test different LLMs and algorithms.
  • Assist in collecting, cleaning, and organizing data sets used for training LLM models.
  • Document the development process, including coding, testing, and deployment procedures.

Details

Work type

Full time

Work mode

hybrid

Start date

Jul 2, 2024

Location

San Francisco