Are you passionate about artificial intelligence and eager to see how generative AI and Machine Learning (ML) can transform real-world business operations? We are seeking a dynamic, self-motivatedEnterprise AI & DevOps Engineering Intern to join our team.
This program offers a unique opportunity to gain hands-on experience researching, building, and scaling AI/ML solutions. As our primary interns, you won't just be sitting on the sidelines—you will learn, develop, and completely own end-to-end applications and deployment pipelines. Sitting at the intersection of full-stack development, cloud infrastructure, and business strategy, you will work closely with experienced mentors and cross-functional teams to drive innovative projects from inception to production. If you are a self-starter who loves to learn, hack on modern tech stacks, and take full ownership of what you build, this is the perfect playground for you.
What You’ll Do
Within 30 Days (Operational Discovery & Deep-Dive):
Operational Deep-Dive: Complete your technical and corporate onboarding, shifting quickly into an exploratory phase to map our enterprise systems, business architecture, and active AI workstreams.
Cross-Functional Discovery: Conduct informational sessions across business units to shadow team members, document operational friction points, and identify high-value opportunities for AI/ML intervention.
Tech & Trend Research and Learning: Dive deep into researching emerging AI/ML technologies, industry trends, and software testing methods, actively learning our internal software development best practices, coding standards, and core development tools.
Value Mapping & Feedback: Synthesize your findings to highlight where generative AI can reduce manual overhead or unlock creative capacity, while providing proactive feedback on optimizing the onboarding experience.
Beyond 30 Days (Own, Build, and Scale):
Rapid Prototyping & Full-Stack Sandbox: Write, debug, and develop full-stack proof-of-concepts (including interactive user interfaces and web pages), leveraging Python backends and JavaScript frontends to build highly responsive, AI-powered tools.
Context Engineering & Model Optimization: Formulate advanced context engineering strategies—optimizing how enterprise data, memory systems, tool outputs, and prompt chaining are orchestrated within the LLM's context window to drive accurate, structured outputs.
End-to-End Pipeline Ownership: Take full ownership of the deployment pipeline. You will design, implement, and maintain robust CI/CD pipelines—automating LLM application deployments and writing automated testing workflows from scratch.
Containerization & Cloud Infrastructure: Get under the hood of modern infrastructure by spearheading containerization efforts with Docker, learning to orchestrate, configure, and manage cloud-based deployments on AWS (EC2, S3, Lambda, and ECS/EKS).
Data Engineering & Analytics: Help clean, organize, and validate datasets for analysis. Support core database tasks like running queries and managing data entry to fuel your deployed ML models.
Observability & Performance Tracking: Monitor cloud system health using tools like AWS CloudWatch, evaluate real-time AI performance against business KPIs, and create visualizations or reports to benchmark user satisfaction.
Tech Showcases & Collaboration: Have fun presenting your hard work! Participate in peer code reviews to learn from senior engineers and showcase your fully operational MVPs during team demo days—translating complex architecture and AI concepts into clear, engaging insights for stakeholders.
Basic Qualifications:
Bachelor's or master's degree in computer science or equivalent
0-2 years knowledge of Full-Stack experience in JavaScript/TypeScript MVC pattern
0-2 years knowledge in DevOps & Automation: Familiarity with automated CI/CD tools, deployment workflows, or Infrastructure as Code (IaC) concepts
Preferred Qualifications:
Coursework & Projects: Previous coursework or practical projects related to DevOps, containers, cloud infrastructure, data engineering, or machine learning application lifecycle management.
Multi-Cloud Awareness: Exposure to foundational cloud computing architecture and cloud-native AI platforms is a plus.
Certifications: Professional cloud computing certifications or training (even if currently in progress) are highly regarded.
Our Values in Action
Embrace the Unknown: Start each day with a "What if?" mindset, ready to tackle unprecedented challenges in applying AI to diverse corporate functions.
Partner with Purpose: Collaborate closely with employees at all levels, putting collective goals ahead of individual recognition.
Passion for People: Focus on developing AI solutions that elevate, augment, and empower our workforce—not replace them.
Collaborate for Success: Thrive in a team environment where teamwork, transparency, and integrity are the foundation of our culture.
What’s in it for You
True Technical Ownership: Skip the busywork. You will build, deploy, and maintain real production-grade pipelines, gaining massive resume-building experience.
Personalized Journeys: Experience a growth-oriented internship with development opportunities and mentorship tailored to your career aspirations.
Purpose-Driven Work: Engage in meaningful, innovative projects that directly impact operational efficiency and drive technological innovation.
Inclusive Culture: Immerse yourself in a values-driven environment that celebrates diverse perspectives, fosters continuous learning, and knows how to celebrate technical wins.
Join us in shaping the future of AI-driven business innovation and employee empowerment!
What do we offer?
We provide competitive and comprehensive benefits to our employees. Below are some highlights of our benefits:
- Medical, Dental, and Vision Insurance Options
- Life and Disability Insurance
- Paid Time-Off
- Parental Benefits
- Compassionate Care Leave
- 401k with Company Match
- Employee Stock Purchase Plan
Learn more about Revvity’s benefits by visiting our Bswift page. Log-In instructions are provided towards the bottom of the Bswift page.
For benefit-eligible roles only. Part-time and temporary roles may not be eligible for all benefits listed. Please reach out to your recruiter for more information.