AI/ML Engineer - Forecasting
Position Summary
We are looking for hands-data scientist/engineer on AI/ML-driven forecasting solutions using large-scale transactional, operational, inventory, and product data.
The initial focus will be developing store-level forecasting and prep planning capabilities that can determine:
• What should be prepared
• How much should be prepared
• When it should be prepared
The ideal candidate will combine strong forecasting and machine learning expertise with modern AI development tools, including LLMs and AI-assisted coding platforms, to rapidly prototype, test, and deploy scalable solutions.
Key Responsibilities
• Develop store-level and item-level demand forecasting models
• Build forecasts at granular intervals such as 15-minute, 30-minute, hourly, and daypart levels
• Translate demand forecasts into actionable operational recommendations
• Build and maintain Python-based data pipelines, feature engineering workflows, training pipelines, and inference logic
• Evaluate multiple forecasting approaches including time-series models, regression, gradient boosting, deep learning, and ensemble techniques
• Use LLMs and AI coding tools to accelerate development, experimentation, testing, documentation, and model iteration
• Perform back-testing, model validation, and performance tuning using historical actuals
• Incorporate internal and external signals such as promotions, holidays, weather, local events, inventory, and recent demand trends
• Develop scalable forecasting frameworks that can support large numbers of stores and products
• Partner with engineering and product teams to operationalize models through APIs and applications
• Continuously monitor model accuracy and improve forecasting performance over time
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field
• Strong hands-on experience building machine learning and forecasting models
• Advanced proficiency in Python and SQL
• Experience with Pandas, Scikit-learn, XGBoost, LightGBM, or similar frameworks
• Experience with time-series forecasting and demand prediction
• Strong understanding of feature engineering, model validation, and back-testing
• Experience working with large-scale transactional or operational datasets
• Experience deploying or productionizing machine learning models
• Strong problem-solving skills with the ability to translate business problems into analytical and technical solutions
Preferred Qualifications
• Experience in retail, restaurants, QSR, hospitality, supply chain, or inventory optimization
• Experience with PyTorch, TensorFlow, or deep learning frameworks
• Experience with cloud data and AI platforms
• Experience building real-time or near-real-time prediction systems
• Experience with demand forecasting, inventory optimization, workforce planning, or operational decisioning
• Experience using LLMs and Generative AI in the software and data science development lifecycle
• Hands-on experience with tools such as GitHub Copilot, Claude Code, Cursor, Codex, or similar AI coding platforms
• Experience with agentic AI workflows, automated experimentation, or AI-assisted model development
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