AI Engineer Intern

Graco manufactures and markets premium equipment to move, measure, control, dispense and spray a wide variety of fluid and powder materials. What does that mean? Well, we pump peanut butter into your jar, and the oil in your car. We glue the soles of your shoes, the glass in your windows and the screen on your phone. We spray the finish on your vehicle, coatings on your pills, the paint on your house and texture on your walls.

Graco is part of your daily life.

The Graco Intern Program offers more than just work experience-it's a chance to make an impact. As an intern, you'll take on projects that matter to the business, contribute to initiatives that drive progress, and develop skills that prepare you for what's ahead. Throughout the program, you'll expand your industry knowledge, collaborate with professionals who are passionate about doing things the right way, and experience a culture that thrives on new ideas and continual growth.

You'll also take part in events designed to support both your learning and personal development. The program concludes with a final presentation where you'll showcase your achievements and the difference you've made.

The AI Engineer Intern position is responsible for assisting in the development, testing, and deployment of Generative AI solutions in collaboration with product managers, software engineers, and cloud architects. The individual in this position will have foundational knowledge of Large Language Models (LLMs) and generative AI technologies with hands-on experience in implementing AI-powered business applications. This role supports the technical implementation of Gen AI solutions on cloud platforms and contributes to solving real-world business problems through innovative LLM-based applications.

What You Will Do:

Generative AI Development

* Participate in the full GenAI development lifecycle including prompt engineering, model fine-tuning, testing, and deployment.

* Assist in developing and maintaining scalable LLM-based applications and generative AI solutions.

* Implement and optimize prompts for various business use cases including content generation, document processing, and intelligent automation.

* Support integration of foundation models (GPT, Claude, LLaMA) and custom LLMs into cloud-based production systems.

* Deploy and manage AI models on cloud platforms (AWS Bedrock, OCI AI Services) to deliver business solutions.

* Document prompt strategies, model configurations, and deployment workflows to ensure reproducibility and adhere to quality standards.

Cross-Functional Partnership

* Work with business stakeholders to understand requirements and design LLM-powered solutions for specific use cases.

* Collaborate closely with cloud engineers, architects, and cross-functional teams to implement GenAI applications.

* Research and experiment with the latest generative AI models, frameworks, and cloud AI services to improve business solutions.

* Stay up to date with emerging LLM technologies, prompt engineering techniques, and cloud AI platform capabilities.

What You Will Bring:

* Currently pursuing or recently completed a degree in Computer Science, Data Science, Artificial Intelligence, or related field.

* Understanding of Large Language Models (LLMs), generative AI concepts, and foundation model architectures.

* Proficiency in Python and familiarity with GenAI frameworks (Lang Chain, Llama Index, Transformers).

* Experience with cloud platforms (AWS, OCI) and AI services (AWS Bedrock, OCI AI Services, Azure OpenAI).

* Knowledge of prompt engineering techniques, model fine-tuning, and LLM optimization strategies.

* Understanding of API integration, microservices architecture, and cloud-native development.

* Strong problem-solving skills with focus on business use case implementation.

* Ability to work independently and collaboratively in a team environment.

* Familiarity with version control systems (Git) and cloud development practices.

Accelerators:

* Experience with advanced prompt engineering, RAG (Retrieval-Augmented Generation) implementations, and vector databases.

* Knowledge of cloud infrastructure (AWS EC2, Lambda, OCI Compute) and serverless architectures for…