Machine Learning Engineer II, Burger King, US&C

Restaurant Brands International Inc. (RBI) is one of the world’s largest quick‑service restaurant companies, operating more than 32,000 restaurants in more than 120 countries. As a Machine Learning Engineer II, you will be part of the Burger King U.S. & Canada team developing and refining machine‑learning models that drive improvements in traffic, profitability and overall restaurant performance. Based in Miami, FL, you will work on site five days per week.

Your role will involve close collaboration with Analytics Engineering, Data Engineering and MLOps teams. What You'll Do: Machine Learning Model Development II: design, develop, and iterate on machine‑learning models, including causal inference, recommendation systems, clustering and optimization models to address high‑impact business problems. Experimentation & Impact Evaluation: partner with Analytics Engineering to design and evaluate experiments (e.g., A/B testing, matched cohorts, difference‑in‑differences) to validate model performance and quantify real‑world impact.

Optimization & Decision Modeling: develop models that inform actionable decisions, including prioritization frameworks and expected-value based optimization to drive improvements in traffic and profitability. Model Evaluation & Continuous Improvement: monitor, evaluate, and refine model performance using statistical methods, backtesting and iterative experimentation to ensure accuracy, stability and sustained impact. Feature Engineering from Curated Data: transform curated datasets into high‑quality model inputs through feature engineering, selection and validation, leveraging domain knowledge and statistical techniques.

Collaboration with Engineering & MLOps: work closely with Analytics Engineering, Data Engineering and MLOps teams to ensure models are production-ready, scalable and effectively integrated into downstream systems. What You'll Bring: 3+ years of experience in machine learning, applied statistics or a related field, with a focus on developing and evaluating models in real‑world applications. Bachelor’s or Master’s degree in Statistics, Economics, Operations Research, Mathematics, Computer Science or a related quantitative field; equivalent applied experience will also be considered.

Strong foundation in statistical modeling and machine learning, with the ability to explain model selection, assumptions and trade‑offs. Experience applying a range of modeling techniques such as regression, clustering, recommendation systems and optimization methods. Familiarity with experimental design and causal inference techniques (e.g., A/B testing, difference‑in‑differences, cohort‑based analysis).

Strong programming skills in Python for analysis and model development. Proficiency in SQL and experience working with large‑scale datasets in Snowflake or a similar cloud data warehouse. Experience working in AWS environments (e.g., SageMaker, EMR) and familiarity with workflow orchestration tools such as Dagster or Airflow.

Benefits: RBI offers a comprehensive global paid parental leave program, free telemedicine and mental wellness support, and benefits focused on physical, mental and financial wellness for employees at all global offices. EEO Statement: Restaurant Brands International and all of its affiliated companies (collectively, RBI) are equal opportunity and affirmative action employers that do not discriminate on the basis of race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability or veteran status or any other characteristic protected by local, state, provincial or federal laws, rules, or regulations. RBI's policy applies to all terms and conditions of employment.

Accommodation is available for applicants with disabilities upon request. #J-18808-Ljbffr