Why This Role Stands Out
This hybrid internship offers a fantastic opportunity to develop cutting-edge AI/ML skills by building data-driven solutions for a leading distributor, gaining exposure to modern tools and cloud platforms within a collaborative, people-first culture. You'll thrive here if you're eager to apply your Python and machine learning fundamentals to real-world challenges, contributing to impactful projects while growing your technical expertise. Apply now to gain invaluable experience in a dynamic industry!
Quick Overview
Job Description
Southern Glazer's Wine & Spirits seeks a 2027 Summer Internship AI Engineer to develop data-driven solutions for wholesale distribution. You'll help design and test ML models for forecasting, routing, and sales optimization using real enterprise datasets. Working with data, IT, and business teams, you'll build prototypes in Python, analyze performance, and present insights. Gain hands-on exposure to modern AI tools, cloud platforms, and MLOps concepts in a collaborative, people-first culture that values learning, inclusion, and community impact across North America.
Responsibilities
- Support design, training, and evaluation of AI/ML models for sales, logistics, and demand forecasting use cases in wholesale distribution
- Assist in data preparation, feature engineering, and model performance analysis using large operational and commercial datasets
- Implement and test prototypes in Python, leveraging modern ML and deep learning frameworks under senior engineer guidance
- Collaborate with data engineers, analysts, and business stakeholders to translate requirements into technical solutions
- Help document models, experiments, and results and contribute to code reviews and best practices
- Build dashboards, reports, or APIs to surface AI insights to internal users across sales and operations
Required Skills
- Python
- Machine learning fundamentals
- Data preprocessing and feature engineering
- SQL and relational databases
- Deep learning frameworks (e.g., Tensor
- Flow or Py
- Torch)
- Data visualization (e.g., Tableau, Power BI, matplotlib)
- Version control with Git
- Cloud platforms (e.g., AWS, Azure, GCP)
- Statistical analysis
- REST APIs or basic software engineering practices
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