AI Application Engineering Intern
Hybrid (Palo Alto, CA)

Groq’s Summer Internship Program runs from May - September and is full-time during the duration of the internship.

Mission: Our promise to customers, partners, and prompters is always and forever to make it real. This internship offers an excellent opportunity to gain firsthand experience in AI application engineering with our Brand Team and a chance to contribute to special projects and initiatives that make Groq real.

As a Brand Team Intern, you will help demonstrate an idea we at Groq call “HumanPlus.” This is when humans, particularly in professional roles, enhance and maximize their skills by seamlessly integrating AI, such as Large Language Models (LLMs), into their creative and work processes. Whether it’s generating code for non-programmers, writing poetically for programmers, or creating images for marketers, LLMs are transforming the way people interact with technology. The ability to interface, communicate, and collaborate with machines using natural language is a powerful aspect of HumanPlus. For more information, check out a recent blog post by Mark Heaps, VP of Brand and Senior Tech Evangelist. 

We are searching for a unique individual who can both showcase their technical skills as an apps engineer and collaborate on content creation. You will work on building demos of AI technology integrated with LLMs, audio models and image generation models to show the potential of HumanPlus when running on the LPU AI Inference Technology by Groq; and you will have the opportunity to present to AI communities and business audiences. You will work cross-functionally with an experienced, dedicated fun team in a dynamic environment that values growth and development. Check out our Showcase page to see examples of applications current and past AI Applications Engineering Interns have built. We look forward to meeting you and providing you with a valuable learning experience.

Responsibilities & opportunities in this role:

• Create real demos showing that the Groq LPU™ AI Inference Technology is the fastest way to run LLMs and other GenerativeAI applications (here [link for "here" https://groq.com/showcases/project-stockbot/] is an example)
• Create examples of Language User Interfaces (LUIs) enabling HumanPlus, demonstrating how individuals take advantage of advancements in AI technology
• Collaborate with Brand and Marketing on content for prompt engineering tutorials, social content, customer API documentation, and user experience feedback to Product
• Attend and support Bay Area industry events including hackathons, developer meetups, and conferences

Ideal candidates have/are:

• Excellent written and verbal communication skills
• Creativity
• Attention to detail
• Familiarity with traditional web technologies such as javascript, html, css. Some web development skills and cloud deployment experience are a big plus.
• Familiarity in building applications that leverage API endpoints such as OpenAI.
• Familiarity with use cases for LLMs on their own or combined with other components such as voice and database.
• Located in the San Francisco Bay Area. Being local to the Bay Area to help support various industry events is a big plus.
• Must be authorized to work in the United States.

Attributes of a Groqster:

• Humility - Egos are checked at the door
• Collaborative & Team Savvy - We make up the smartest person in the room, together
• Growth & Giver Mindset - Learn it all versus know it all, we share knowledge generously
• Curious & Innovative - Take a creative approach to projects, problems, and design
• Passion, Grit, & Boldness - no limit thinking, fueling informed risk taking

If this sounds like you, we’d love to hear from you!

Compensation: The US pay range for our technical internships is $30-$50 / per hour. The US pay range for our non-technical internships is $30-$40 / per hour. Individual compensation will be commensurate with the candidate’s qualifications and experience, country of internship and aligned with Groq’s internal leveling guidelines and benchmarks. #LI-DNI