AI Backend Engineer II
Summary
The AI Backend Engineer II builds and maintains the production software systems and infrastructure required to deploy and scale machine learning models. The role focuses on integrating AI capabilities into business workflows using Python, containerization, and message streaming technologies.
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 AI Backend Engineer II to join our dynamic team at Yum Brands. As an AI Backend Engineer II, you will build the production software systems, services, and infrastructure that power machine learning solutions at scale. You will focus on deploying, integrating, and operating AI capabilities across our business, ensuring they are reliable, scalable, and performant in production environments.
Key Responsibilities:
Collaborate with data scientists, software engineers, and business stakeholders to deploy, integrate, and operate machine learning solutions within production systems and business applications.
Design, develop, and maintain scalable production systems that deploy, serve, monitor, and integrate machine learning models into downstream applications and business workflows.
- Optimize machine learning platforms, services, and deployment pipelines for performance, scalability, reliability, and operational efficiency.
- 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) designing, building, and operating production software systems that support machine learning solutions in real-world business applications.
- Experience working with distributed systems, APIs, and microservices in production environments.
- 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:
- Experience with cloud computing platforms such as AWS, Azure, or GCP.
- Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.
Experience with version control systems, such as Git.