The board
- Hours
- Full time
- Where
- Chicago IL USA
- Apply by
- End Date: December 31, 2026
- Posted
- Sep 2
The AI Engineering Intern (Intern) supports the design, development, testing, and deployment of artificial intelligence solutions across the organization. This hands-on role provides exposure to core AI engineering practices—including model development, data preparation, and prototype creation—while contributing to supervised project tasks. Working closely with senior engineers, the intern builds foundational skills in coding standards, version control, evaluation techniques, and cloud-native development workflows. The intern collaborates with cross-functional teams, applies academic concepts to enterprise-scale systems, and gains the experience needed to grow into an entry-level engineering role.
This role emphasizes learning and skill development while delivering on assigned components, working under close supervision with frequent check-ins and code reviews, and building foundational…
What you'd do
- Support the development of AI models and prototypes through data preparation, scripting, and experimentation
- Assist in implementing components of AI pipelines, including preprocessing, model training, and testing workflows
- Participate in code reviews and supervised engineering tasks to learn best practices
- Contribute to documentation of prototypes, experiments, and engineering processes
- Execute test cases and validation procedures to verify model performance and reliability
- Analyze datasets to extract insights and generate features under guidance
- Learn cloud-based tools, containerization, and orchestration concepts relevant to AI deployment
- Collaborate with team members to solve technical problems and complete scoped tasks
- Follow established coding, security, and compliance guidelines
- Explore emerging AI technologies and frameworks to build foundational understanding
What they want
- Pursuing a degree in Computer Science, Engineering, Data Science, or a related field
- Working knowledge of foundational programming concepts and data structures, with exposure to Python
- Familiarity with core AI/ML concepts gained through coursework or independent projects
- Ability to communicate technical ideas clearly and collaborate effectively within a team
- Exposure to cloud platforms such as AWS, Azure, or GCP, along with containerization concepts including Docker and Kubernetes
- Introductory understanding of CI/CD practices and distributed computing fundamentals
- Curiosity-driven approach to learning, with responsiveness to feedback and coaching
- Some grounding in generative AI frameworks such as PyTorch, TensorFlow, or Hugging Face
- Beginning awareness of LLM concepts, including RAG workflows, vector databases, and fine-tuning techniques
- Starts
- 2026-08-20