Sr Machine Learning Engineer
Yum! Brands, Inc.2 months ago
Irvine, CA, USASenior
Base Salary
$130k - $162k/yr
Responsibilities
- Deploy, monitor, maintain, and improve production machine learning workflows for media measurement and customer analytics.
- Develop and maintain SageMaker processing and training jobs, model endpoints, and supporting infrastructure across development, testing, and production environments.
- Contribute to Step Functions, Lambda, and Airflow workflows for model training, scoring, retraining, and analytics pipelines.
- Support MLflow model registration and promotion, configuration management, and versioned model artifacts.
- Build and maintain Docker images, ECR repositories, and GitLab pipelines for model deployment and release processes.
- Productionize machine learning models and data pipelines supporting customer analytics, scoring, and decisioning use cases.
- Investigate and resolve production issues using CloudWatch, DataDog, SageMaker logs, and workflow monitoring tools.
- Collaborate with Data Scientists, Data Engineers, Analytics stakeholders, and other technical and non-technical partners on platform enhancements and new capabilities.
- Contribute to engineering best practices, documentation, testing strategies, and operational procedures.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, Data Science, or a related field.
- At least 3 years of experience in Machine Learning Engineering, MLOps, Software Engineering, or related technical roles.
- Strong Python development skills with pandas, PyTorch, scikit-learn, boto3, and SQL.
- Experience with AWS services including 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.
- Preferred 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 Terraform, Terragrunt, or CloudFormation.
- Preferred experience with customer analytics, marketing measurement, or recommendation systems.
Benefits
- Medical, dental, vision, legal, and accidental death and dismemberment insurance options for employees and eligible family members.
- FSA/HSA options depending on the enrolled medical plan.
- Short-term disability, long-term disability, and life insurance.
- 401(k) plan.
- Four weeks of vacation, paid sick leave, 10 paid holidays, a floating day off, and two paid volunteer days per calendar year.
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