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Eragon

Applied AI Intern

Posted 3 Days Ago
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In-Office
San Francisco, CA, USA
Internship
In-Office
San Francisco, CA, USA
Internship
Supports the development and deployment of production AI systems by fine-tuning and evaluating machine learning models, integrating AI features, working with training and evaluation data, running experiments, monitoring performance, and collaborating with engineering and product teams. Requires current enrollment in a relevant bachelor's or master's program, Python proficiency, familiarity with PyTorch or TensorFlow, and foundational machine learning knowledge.
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Job Description

We’re looking for an Applied AI Intern to help build and deploy production-grade AI systems. In this role, you’ll work closely with engineers and researchers to take models from concept to real-world applications.

You’ll gain hands-on experience working across modeling, data, and systems, contributing to projects that ship to real users.

Key Responsibilities
  • Model Development: Assist in fine-tuning, evaluating, and applying machine learning models to real-world problems

  • System Implementation: Help build and integrate AI-powered features into production systems

  • Data & Pipelines: Work with datasets to support training, evaluation, and iteration

  • Experimentation: Run experiments, analyze results, and iterate on model performance

  • Evaluation & Monitoring: Contribute to evaluation frameworks and help track system performance

  • Cross-Functional Collaboration: Work with engineering and product teams to support feature development

Minimum Qualifications
  • Education: Currently pursuing a Bachelor’s or Master’s in Computer Science, Engineering, or a related field

  • Technical Skills: Proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow)

  • ML Fundamentals: Understanding of basic machine learning concepts and workflows

  • Problem Solving: Ability to break down problems and contribute to practical solutions

  • Curiosity & Ownership: Strong desire to learn and contribute in a fast-paced environment

Nice to Have
  • Experience with ML projects, internships, or research

  • Familiarity with LLMs, agents, or data pipelines

  • Experience building projects outside of coursework

  • Interest in working on real-world AI applications

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