Applied AI & Analytics Intern: Build Real-World ML

PassFort

Newark (CA)

On-site

USD 40,000 - 57,000

Full time

5 days ago
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Job summary

Moody's in the United States invites students to join the 10-week Data Platform internship, working on AI tooling, language models, and predictive models within a collaborative team. You'll gather and analyze operational data, design models for job runtimes and queue wait times, and document results while gaining hands-on experience in responsible AI practices and cloud platforms such as AWS.

This paid, full-time internship runs June–August 2027 and offers mentorship, networking, and real

Qualifications

  • Pursuing a quantitative degree with 2027–2028 graduation.
  • Strong Python and ML libraries experience.
  • Interest in queuing theory and capacity analysis.
  • Experience with large language models/AI tooling.
  • Familiar with cloud platforms like AWS.

Responsibilities

  • Build AI solutions within a data platform team including LLMs and predictive models.
  • Drive an AI initiative from concept to measurable outcome during internship.
  • Design AI solutions using large language models and retrieval augmentation.
  • Gather, clean and analyse operational data to identify trends and baselines.
  • Develop and evaluate predictive models for runtimes, queue wait times and capacity requirements.

Skills

Python
ML/AI concepts
Statistics
SQL
Cloud (AWS)
Linux CLI
Problem solving
Communication

Education

CS/Data Science degree
Graduation 2027–2028

Tools

Git
APIs
RAG tooling

Job description

Moody's in the United States invites students to join the 10-week Data Platform internship, working on AI tooling, language models, and predictive models within a collaborative team. You'll gather and analyze operational data, design models for job runtimes and queue wait times, and document results while gaining hands-on experience in responsible AI practices and cloud platforms such as AWS.

This paid, full-time internship runs June–August 2027 and offers mentorship, networking, and real

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