Summary: We are looking for a motivated and curious AI Technical Program Intern to join our team. This is a hands-on role designed for students who want real exposure to how AI is built, tested, and applied in a business environment.
You will work on new AI initiatives, collaborating closely with AI engineers, data scientists, and business stakeholders. The role is best suited for candidates interested in an AI Engineer / Data Scientist career path and who enjoy turning ambiguous problems into working prototypes.
What You'll Deliver
Over the 6-month internship, you are expected to deliver either a well-defined proof of concept (POC) or a shipped prototype, depending on project scope, complexity, and readiness.
Deliverables may include:
- A validated POC, including problem framing, data exploration, model experimentation, evaluation results, and documented findings, or
- A shipped or near-production prototype, such as a working ML model or GenAI application, with clear technical documentation and handover materials
Example deliverables may include:
- A prototype that extracts structured data from unstructured documents
- An analytical or ML-based solution that identifies patterns or optimization opportunities in operational or business datasets
- A GenAI-powered internal tool or workflow prototype to support productivity or decision-making
Employment Type: Internship - 6 Months
Reports to: Senior Manager, AI Technical Program
Role and Responsibilities:
- Assist in designing, developing, training, and evaluating machine learning or GenAI models for real business problems
- Perform data collection, cleaning, preprocessing, and exploratory data analysis
- Prototype AI solutions rapidly using notebooks, scripts, or lightweight applications
- Research emerging AI techniques, tools, and frameworks and share insights with the team
- Support basic data pipelines, experimentation workflows, and model evaluation
- Document assumptions, experiments, results, and limitations clearly
- Collaborate with cross-functional teams to translate business questions into technical tasks
Requirements:
- Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field
- Comfortable using Python for data analysis and experimentation
- Foundational understanding of machine learning concepts (e.g. supervised vs. unsupervised learning, model evaluation)
- Familiarity with common data analysis libraries (Pandas, NumPy, Matplotlib or similar)
- Strong analytical thinking and problem-solving skills
- Clear communication skills and ability to explain technical ideas simply
- Self-driven, curious, and eager to learn
- Exposure to ML frameworks such as scikit-learn, PyTorch, or TensorFlow
- Coursework or personal projects in NLP, computer vision, or generative AI
- Experience working with SQL or structured datasets
- Familiarity with Git or version control workflows
- Awareness of cloud platforms (AWS, GCP, or Azure), even at a conceptual level
