We’re looking for a Senior AI Engineer I to help design, build, and scale our next generation promotion optimization and forecasting platform. This role sits at the intersection of machine learning, data science, and applied statistics, focusing on personalized promotions, price elasticity modeling, and demand forecasting across thousands of SKUs. You’ll work closely with data engineers, product managers, and marketing analytics to design AI driven decision systems that maximize business impact while ensuring technical excellence and scalability. Duties & Responsibilities Forecasting & Modeling • Develop and deploy time-series forecasting models (e.g., Prophet, ARIMA, DeepAR, LSTM, Temporal Fusion Transformer) to predict demand, revenue, and promotion lift. • Apply advanced statistical and causal-inference methods to understand promotion effects and seasonality. • Build dynamic pricing and promotion recommendation models leveraging reinforcement learning or multi armed bandits. AI System Design • Architect ML pipelines for promotion targeting and ROI optimization • Design end to end data workflows from data ingestion to model deployment integrated with production APIs and dashboards. • Contribute to scalable model monitoring, retraining, and drift detection. Data Engineering & APIs • Work with SQL databases, data warehouses (Azure SQL, Snowflake, Databricks Delta, etc.), and APIs to retrieve, transform, and operationalize data. • Collaborate with cloud teams to ensure efficient and secure deployment of AI services (Azure or GCP). The ideal candidate should have a background that demonstrates strong technical and solution experience designing and building systems that consider careful technology selection, security, interfaces, performance, stability, security, and economy of operation. Experience within the retail domain is highly desired. Requirements Basic Qualifications • Master’s degree in computer science, Data Science, Statistics, or a related field. • 6+ years of experience in designing, developing, and deploying AI/ML solutions. • Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). • Strong expertise in forecasting and time series analysis techniques. • Solid understanding of machine learning algorithms and statistical modeling. • Experience with data preprocessing, feature engineering, and model evaluation. • Familiarity with version control systems (e.g., Git) and collaborative development workflows. • Strong problem-solving and analytical skills.