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Full-Stack AI Developer Intern at Revvity – Remote AI and Full-Stack Internship with LLM Applications

Full-Stack AI Developer Intern at Revvity – Remote AI and Full-Stack Internship with LLM Applications

Sourced from revvity.wd103.myworkdayjobs.com

AI Dev Intern

Remote
Full-Time
Posted April 20, 2026
Salary
40K-65K/Month
Batches
2026,2027
Apply Route
100% Direct

About The Role

Revvity is a global science and health technology company that develops advanced solutions for researchers, clinicians, and laboratories working to solve critical health and life sciences challenges. With thousands of professionals worldwide, the company combines scientific innovation, enterprise software, and digital transformation to improve healthcare workflows and research productivity. Its growing focus on enterprise AI includes using large language models, automation tools, and intelligent systems to improve internal productivity and decision-making across business operations. This internship offers practical exposure to applied generative AI inside a global innovation-driven environment where AI solutions are connected to real enterprise needs 🧠💻

Responsibilities

Develop prototypes and proof-of-concepts for AI-powered productivity features.
Assist in fine-tuning and optimizing large language models for enterprise use cases.
Support prompt engineering strategies for business-focused AI applications.
Contribute to AI tools integrated with internal workflow systems.
Participate in model integration projects across digital platforms.
Help evaluate AI model performance against business and usability metrics.
Present technical findings clearly to technical and non-technical stakeholders.
Collaborate across departments to identify practical AI opportunities.

Requirements

  • Strong interest in enterprise AI and generative AI applications.
  • Familiarity with large language models such as ChatGPT or Claude.
  • Knowledge of Python, Next.js, Docker, and full-stack development fundamentals.
  • Basic understanding of prompt engineering concepts.
  • Familiarity with machine learning frameworks such as TensorFlow or PyTorch.
  • Strong problem-solving ability and attention to detail.
  • Good written and verbal communication skills.

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