Applied AI Intern
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Older posting · still listed ·
- Work arrangement
- onsite
- Employment
- FullTime
- Stated compensation
- USD 1,000–2,000 1 WEEK
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Requirements
1 with evidence8 unclear or unstated- Remote policy
- onsite
“Provider workplace type: onsite”
From employer posting metadata - Employment type
- FullTime
- Compensation
- USD 1,000–2,000 1 WEEK
8 fields not stated in this posting
- Employer sponsorship
- Not specified
- Geographic scope
- Not specified
- Degree requirement
- Not specified
- Security clearance
- Not mentioned
- Timezone / hours
- Not specified
- Citizenship requirement
- Not mentioned
- Minimum experience (years)
- Not specified
- Work authorization
- Not specified
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Original job description
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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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