Sr Machine Learning Engineer
Yum!
- Irvine, California, United States · Plano, Texas, United States · Louisville, Kentucky, United States
- Hybrid
- $129,800 - $162,200 a year
- Posted Jun 8, 2026
Job description
About the role
The Senior Machine Learning Engineer will design, deploy, and maintain AWS‑based machine learning platforms for media measurement and customer analytics, partnering closely with data scientists, data engineers, and analytics stakeholders to ensure reliable, scalable production ML workflows.
About the company
Yum! Brands, a global restaurant and foodservice company that includes subsidiaries such as Yum Restaurant Services Group and Yum Digital & Technology, focuses on delivering consumer experiences through its restaurant brands and invests in digital and technology capabilities; the company emphasizes its core value of "Believe in ALL People" and is committed to equity, inclusion and belonging.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field
- 3+ years of experience in Machine Learning Engineering, MLOps, Software Engineering, or related technical roles
- Strong Python development skills, including experience with pandas, PyTorch, scikit-learn, boto3, and SQL
- Experience with AWS services such as SageMaker, Step Functions, Lambda, S3, IAM, and ECR
- Experience developing or supporting orchestration workflows using Airflow, Glue, or similar technologies
- Familiarity with cloud‑based data platforms such as Snowflake, Redshift, or Athena
- Experience with Docker, CI/CD pipelines, source control workflows, and software development best practices
- Strong troubleshooting and debugging skills across distributed systems and machine learning workflows
- Ability to collaborate effectively with technical and non‑technical stakeholders
- Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ (preferred)
- Familiarity with MLflow, Hydra/OmegaConf, FastAPI, or similar ML platform tooling (preferred)
- Experience supporting deep learning workflows in production environments (preferred)
- Exposure to infrastructure‑as‑code tools such as Terraform, Terragrunt, or CloudFormation (preferred)
- Experience working with customer analytics, marketing measurement, or recommendation systems (preferred)