Full Stack AI Developer

Revvity

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.

### **The Big Picture**

Join the RevvityAI development team to design, build, and improve software that helps power AI\-driven capabilities. They will help translate product needs into reliable systems, contribute to model\- and data\-focused engineering, and support continuous improvement across the stack.

### **What's in it for you**

• Experience personalized career journeys with growth\-oriented development opportunities.
• Engage in purpose\-driven work that makes a positive impact on society.
• Be part of a values\-driven culture that encourages collaboration and fresh ideas.
• Placeholder for local benefits

### **Your Superpowers in Action**

• Design, develop, and maintain AI\-enabled applications and services using modern software engineering practices.
• Build and optimize data pipelines and machine learning workflows that improve performance, reliability, and usability.
• Collaborate with product and engineering partners to translate requirements into clear technical solutions.
• Write clean, testable code and help establish engineering standards for performance, security, and maintainability.
• Monitor deployed systems, troubleshoot issues, and iterate based on real\-world feedback and metrics.

### **Basic qualifications**

• Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience).
• Strong programming skills in at least one modern language such as Python, Java, or C\#.
• Experience building software services using APIs, databases, and version control.

### **Preferred qualifications**

• Experience with machine learning or AI frameworks and developing production ML workflows.
• Familiarity with cloud services, containerization, and deployment practices.
• Experience with data engineering tasks such as ETL/ELT, data quality checks, and performance tuning.