Tech & IT

Orbit Lab-to-Product AI CV

Built for candidates moving from research labs into product-focused AI teams and needing both academic and practical proof.

๐Ÿ’ป
Rating
4.8
Format
Google Docs
Pages
2
Experience
Any Level
ATS-Friendly
โœ“ Yes
Color
Tech Blue
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About this template

Orbit Lab-to-Product AI CV is designed for professionals who are translating research expertise into product outcomes. The layout starts with a succinct summary that bridges theory, experimentation, and business relevance, then moves into projects and experience with room for metrics, deployment notes, and collaboration context. It is a strong fit for candidates whose work spans labs, startups, and applied AI teams.

One of the templateโ€™s strengths is its ability to present applied AI projects without losing the academic credibility of papers or competition results. You can include publications, Kaggle rankings, demo links, and prototype outcomes in separate blocks that remain easy to scan. The format is also ATS-friendly, using standard headings and straightforward text flow so automated systems can identify the right keywords.

Use this CV when you want to show that your research can ship. It works well for candidates with internships, assistantships, open-source contributions, or side projects that evolved into product features. Add links to notebooks, papers, or GitHub repositories, and tailor the summary to the domain you are targeting, such as vision, NLP, or recommendation systems. The result is a balanced profile for modern AI hiring pipelines.

Key features

  • Applied AI projects section bridges research and product work
  • ATS-friendly headings improve parsing and keyword matching
  • Publications, Kaggle, and demos can live in separate blocks
  • Summary emphasizes business relevance and collaboration
  • Two-page structure supports mixed academic and applied evidence

Best for

  • โ†’ Researchers moving into product AI roles
  • โ†’ Engineers with papers and demo projects
  • โ†’ Candidates combining Kaggle and internship experience

Sections included

  • โœ“ Header with portfolio and contact links
  • โœ“ Summary bridging research and product
  • โœ“ Projects with metrics and demo links
  • โœ“ Publications, Kaggle results, and awards
  • โœ“ Skills, education, and open-source contributions

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