Job Category: Artificial Intelligence
Job Type: Internship
Job Location: Remote / Hybrid U.S. -based

Duration : 2 months, starting July

About the Program

This Summer Internship Program is designed for AI engineers, data scientists, and product-minded technical candidates who want to learn how to apply their skills in real-world business and enterprise environments.

The program focuses on helping technically strong candidates grow into forward-deployed engineers: people who can understand business problems, work directly with stakeholders, define product requirements, build practical AI-enabled solutions, and communicate clearly across technical and non-technical teams.

This is not a passive learning program. Participants will be expected to think, build, document, present, and iterate.

What You Will Learn

During the program, participants will be trained on:

  1. Applying AI and data science skills to real-world business problems
  2. Working like a forward-deployed engineer in product-facing and stakeholder-facing environments
  3. Understanding user needs, business goals, and delivery constraints
  4. Turning ambiguous problems into structured product requirements
  5. Building AI-enabled workflows, prototypes, and solution concepts
  6. Designing solutions with enterprise readiness in mind
  7. Communicating technical work to business and non-technical stakeholders
  8. Thinking like both an engineer and a product manager

What You May Work On

Depending on fit and project needs, participants may contribute to:

  1. AI workflow prototypes
  2. Data science and analytics use cases
  3. Agentic AI experiments
  4. Product requirement documents and solution designs
  5. Internal tools, demos, or proof-of-concept builds
  6. Research and technical documentation
  7. Enterprise AI implementation planning
  8. Product discovery, user workflows, and delivery roadmaps

Who This Is For

This program is intended for technically capable candidates who are early in their professional journey and want to build practical experience beyond coursework, academic projects, or early industry exposure.

Strong candidates may come from backgrounds in:

  1. AI engineering
  2. Data science
  3. Machine learning
  4. Analytics
  5. Software engineering
  6. Technical product development
  7. Applied research
  8. Business technology or consulting

We are looking for people who are curious, execution-focused, clear communicators, and comfortable working in ambiguous environments. A perfect resume is not required. Practical thinking, strong learning ability, and willingness to build matter more.

Preferred Experience

Strong candidates may have experience with one or more of the following:

  1. Python, SQL, or data analysis
  2. Machine learning, LLMs, agentic AI, or AI automation
  3. Academic, internship, or industry projects
  4. Product development or startup projects
  5. Cloud tools, APIs, or workflow automation
  6. Data visualization or business intelligence
  7. Technical writing or product documentation
  8. Client-facing, consulting, or cross-functional project work

What You Will Gain

By the end of the program, participants should have a stronger understanding of:

  1. How AI projects move from idea to usable product
  2. How enterprise-ready solutions are designed and evaluated
  3. How forward-deployed engineers work with business and technical stakeholders
  4. How to approach product requirements, delivery planning, and implementation
  5. How to communicate technical work in a professional setting
  6. How to build practical AI-enabled prototypes and solution concepts

Bio Section Guidance

In the bio section of the application form, please include:

  1. Your education background and current academic or professional status
  2. Your interests in AI, data science, product building, or forward-deployed engineering
  3. Any relevant academic, internship, industry, research, or project experience
  4. Examples of products, prototypes, models, tools, automations, dashboards, papers, or technical work you have built or contributed to
  5. Links to your portfolio, GitHub, LinkedIn, personal website, demos, or project write-ups, if available
  6. A short note on what you hope to learn or build through this program

Apply for this position

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