AI Intern global Operations

Revvity•Waltham, MA

23h•$20 - $30

About The Position

Revvity is a developer and provider of end-to-end solutions designed to help scientists, researchers, and clinicians solve the world’s greatest health challenges. We pair the enthusiasm of an industry disruptor with the experience of a longtime leader. Our team of 11,000+ colleagues from around the globe are vital to our success and the reason we’re able to push boundaries in pursuit of better human health. Find your future at Revvity AI Intern – Global Operations About You: You’re an engineer at heart who’s passionate about how AI, generative models, and automation can enhance global operations . You enjoy turning ideas into prototypes, integrating data systems, and applying AI to solve real business problems. You’re curious, collaborative, and motivated to deliver measurable impact across supply chain, manufacturing, and service operations. You work well across technical and functional boundaries, translating business pain points into workable AI solutions. You value transparency and collective success, thriving in globally distributed, fast-moving environments. What You’ll Do Within 30 Days Complete onboarding and get familiar with Revvity’s enterprise systems, data architecture, and current AI initiatives. Set up your development environment (GitHub, Docker, Next.js, internal APIs), and review existing AI integrations. Shadow data and operations analysts to understand how information flows across global functions. Identify early opportunities for process automation or AI augmentation. Beyond 60 Days Build and iterate AI prototypes and proof-of-concepts that automate or enhance business processes (e.g., reporting, forecasting, supplier interactions). Develop data pipelines and retrieval layers to connect AI tools with enterprise data sources. Implement prompt engineering and RAG-based workflows for internal search, summarization, and decision support. Prototype AI assistant interfaces or agent workflows integrated with ERP and operations platforms. Evaluate model behavior—accuracy, latency, bias, and business impact—using clearly defined metrics. Collaborate with DevOps and IT teams to ensure deployment scalability and security. Present your work to both technical and operational leaders, translating AI capabilities into operational outcomes. This internship offers a hands-on opportunity to design, build, and test AI-powered solutions embedded within a global enterprise environment. You’ll collaborate across data, operations, and engineering teams to bring next-generation AI capabilities into real business contexts, turning experimentation into measurable transformation.

Requirements

Strong interest in AI for enterprise operations and digital transformation .
Solid experience with Python and API development (REST or GraphQL).
Understanding of LLMs and related stacks (embeddings, vector databases, fine-tuning workflows).
Familiarity with Next.js, React, or TypeScript for internal tooling or prototype UIs.
Proficiency with Docker and foundational cloud deployment (Azure, GCP, or AWS).
Exposure to data processing and pipeline design (pandas, SQL, or similar).
Comfortable working with ambiguity and learning quickly in fast-moving projects.

Nice To Haves

Experience with ERP integration (SAP, Oracle) or workflow automation tools like ServiceNow or Power Automate.

Responsibilities

Build and iterate AI prototypes and proof-of-concepts that automate or enhance business processes (e.g., reporting, forecasting, supplier interactions).
Develop data pipelines and retrieval layers to connect AI tools with enterprise data sources.
Implement prompt engineering and RAG-based workflows for internal search, summarization, and decision support.
Prototype AI assistant interfaces or agent workflows integrated with ERP and operations platforms.
Evaluate model behavior—accuracy, latency, bias, and business impact—using clearly defined metrics.
Collaborate with DevOps and IT teams to ensure deployment scalability and security.
Present your work to both technical and operational leaders, translating AI capabilities into operational outcomes.