Applied AI Intern
AI summary of the role
Applied AI Intern assists in building and deploying production-grade AI systems, working across modeling, data, and systems.
What you’ll do
- Assist in fine-tuning, evaluating, and applying ML models
- Build and integrate AI features into production systems
- Work with datasets for training, evaluation, and iteration
- Run experiments, analyze results, and iterate on performance
What you’ll bring
- Pursuing Bachelor’s or Master’s in CS, Engineering, or related
- Proficiency in Python
- Familiarity with ML frameworks (PyTorch, TensorFlow)
- Understanding of basic ML concepts and workflows
Technologies
PyTorch · TensorFlow · Python · LLMs · agents · data pipelines
About Eragon
AI operating system that connects company systems, trains business-specific models, and deploys agents that learn from real workflow feedback inside customer-controlled environments.
Seed · 1–10 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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
More from the job description
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
Employer postings · Data from · Sources