Sr Machine Learning Engineer

Posted 2 Days Ago
Be an Early Applicant
3 Locations
Hybrid
130K-162K Annually
Senior level
Food
The Role
Deploy, maintain, and improve production ML workflows and platforms for media measurement and customer analytics on AWS. Build SageMaker jobs and endpoints, orchestrate pipelines with Step Functions, Lambda, and Airflow, manage model artifacts and CI/CD, troubleshoot production issues, and collaborate on platform enhancements and operational best practices.
Summary Generated by Built In

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data Scientists, Data Engineers, and Analytics stakeholders to deploy, maintain, and improve production ML workflows across AWS. The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for building reliable, scalable machine learning systems.

Responsibilities
  • Support the deployment, monitoring, and ongoing maintenance of media measurement and customer modeling systems in partnership with Data Science and Engineering teams. 
  • Develop and maintain SageMaker processing and training jobs, model endpoints, and supporting infrastructure across development, testing, and production environments. 
  • Contribute to Step Functions, Lambda functions, and Airflow (MWAA) workflows that orchestrate model training, scoring, retraining, and analytics pipelines. 
  • Support MLflow model registration and promotion processes, configuration management, and versioned model artifacts. 
  • Build and maintain Docker images, ECR repositories, and GitLab CI/CD pipelines to enable reliable model deployment and release processes. 
  • Help productionize machine learning models and data pipelines that support customer analytics, scoring, and decisioning use cases. 
  • Investigate and resolve production issues using CloudWatch, DataDog, SageMaker logs, and workflow monitoring tools. 
  • Collaborate with cross-functional partners to implement platform enhancements, improve operational reliability, and deliver new capabilities. 
  • Contribute to engineering best practices, documentation, testing strategies, and operational procedures. 
Qualifications

Required Qualifications

  • 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 working 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. 

Preferred Qualifications

  • Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. 
  • Familiarity with MLflow, Hydra/OmegaConf, FastAPI, or similar ML platform tooling. 
  • Experience supporting deep learning workflows in production environments. 
  • Exposure to infrastructure-as-code tools such as Terraform, Terragrunt, or CloudFormation. 
  • Experience working with customer analytics, marketing measurement, or recommendation systems. 

 

Salary Range: 129,800 - 162,200 annually + bonus eligibility. This is the expected salary range for this position. Ultimately, in determining pay, we'll consider the successful candidate’s location, experience, and other job-related factors.

Benefits: Employees (and their eligible family members) may enroll in the following types of insurance coverage: medical, dental, vision, legal, and accidental death and dismemberment, as well as FSA/HSA (depending on enrolled medical plan). Yum! also provides short-term disability, long-term disability, and life insurance. Employees may enroll in our 401(k) plan. Yum! provides 4 weeks of vacation, paid sick leave, 10 paid holidays, a floating day off and 2 paid days for volunteer time each calendar year. To learn more about working at Yum! -Click here. 

At Yum!, one of our core values is to Believe in ALL People. This means seeing the value in everyone and unlocking their full potential to be their best self. YUM! Brands, Inc. (including its subsidiaries Yum Restaurant Services Group, LLC (“YRSG”) and Yum Connect, LLC (“Yum Digital and Technology”)(collectively, “Yum”) is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity.  We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic. Yum! is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs.

US Job Seekers/Employees - Click here to view the “Know Your Rights” poster and supplement and the Pay Transparency Policy Statement.

Skills Required

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field
  • 3+ years of experience in Machine Learning Engineering, MLOps, Software Engineering, or related technical roles
  • Strong Python development skills including pandas, PyTorch, scikit-learn, boto3, and SQL
  • Experience with AWS services: 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 ML workflows
  • Ability to collaborate effectively with technical and non-technical stakeholders
  • Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ
  • Familiarity with MLflow, Hydra/OmegaConf, FastAPI, or similar ML platform tooling
  • Experience supporting deep learning workflows in production environments
  • Exposure to infrastructure-as-code tools such as Terraform, Terragrunt, or CloudFormation
  • Experience working with customer analytics, marketing measurement, or recommendation systems

Yum! Brands Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Yum! Brands and has not been reviewed or approved by Yum! Brands.

  • Leave & Time Off Breadth Corporate roles include four weeks of vacation, year‑round half‑day Fridays, company holidays, dedicated “Live Well” days, and paid volunteer days. These policies contribute meaningfully to overall compensation value for corporate employees.
  • Wellbeing & Lifestyle Benefits Offerings include free access to mental‑health counselors, onsite/virtual wellness tools, onsite gyms in select offices, and wellbeing discounts. Smoking‑cessation and weight‑management programs further bolster lifestyle support.
  • Parental & Family Support Benefits span family‑planning coverage such as adoption, fertility, and baby‑bonding leave. Corporate materials also note enhanced parental leave for U.S. corporate employees.

Yum! Brands Insights

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The Company
HQ: Louisville, KY
6,056 Employees
Year Founded: 1997

What We Do

Yum! Brands, Inc., based in Louisville, Kentucky, and its subsidiaries franchise or operate a system of over 55,000 restaurants in more than 155 countries and territories under the Company’s concepts – KFC, Taco Bell, Pizza Hut and the Habit Burger Grill. The Company's KFC, Taco Bell and Pizza Hut brands are global leaders of the chicken, Mexican-style food, and pizza categories, respectively. The Habit Burger Grill is a fast casual restaurant concept specializing in made-to-order chargrilled burgers, sandwiches and more. What makes Yum! a great place to work? It's our people. As the world's largest restaurant company, we invest in people capability so that our global workforce can make the most of their careers. With ongoing opportunities for personal and professional success, we've built a culture that rewards and recognizes great effort while providing the flexibility that is so important to all of us.

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