Machine Learning Engineer II

 

Company Overview:

Yum Brands is a global leader in the fast-food industry, with a portfolio of renowned brands including KFC, Pizza Hut, Taco Bell, and more. We're dedicated to providing delicious, convenient, and innovative food experiences to our customers worldwide.

 

Position Overview:

We are seeking a talented and passionate Machine Learning Engineer to join our dynamic team at Yum Brands. As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from customer experience optimization to supply chain management.

Key Responsibilities:

• Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to identify opportunities for leveraging machine learning techniques to drive business outcomes.
• Design, develop, and deploy scalable machine learning models and algorithms that address business challenges and improve operational efficiency.

• Optimize machine learning models for performance, scalability, and efficiency.

• Build robust data pipelines and infrastructure to support the training and deployment of machine learning models in production environments.
• Work with DevOps teams to automate deployment processes, monitor system performance, and ensure the smooth operation of applications and services in production.
• Stay updated on emerging technologies and industry trends in machine learning, software engineering, and cloud computing, and evaluate their potential impact on our business operations.

Qualifications:

• Bachelor’s or master’s degree in computer science, engineering, mathematics, or a related field.
• Proven experience (4+ years) in developing and deploying in production environments, preferably in the context of real-world business applications.
• Proficiency in Python with strong software engineering skills and experience in building scalable and maintainable code.
• Proficiency in message queue technologies and services like Kafka, Pulsar, or RabbitMQ and experience working with real-time data streaming.
• Experience working with containerization technologies such as Docker and Kubernetes.
• Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
• Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced and dynamic environment.

 

Nice to Have:

• Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.
• Experience with cloud computing platforms such as AWS, Azure, or GCP.

• Experience with version control systems, such as Git.

 

Salary Range: 105,500 - 132,200

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, half day Fridays year-round 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.

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