GenAI ML/LLM Operations Engineer

Mondelēz International; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Mondelēz International seeks a GenAI Ops Engineer to enhance AI capabilities within a transformative environment. This role involves managing GenAI pipelines, collaborating with teams, and optimizing performance to support future innovations. If you have a strong foundation in AI and cloud technologies, apply to join us in leading the future of snacking.

Qualifications

• Proficient in GCP services and containerization technologies.
• Experience in deploying generative AI models in cloud environments.
• Strong understanding of security best practices.

Responsibilities

• Deploy, monitor, and maintain generative models in production.
• Evaluate and compare various GenAI models based on criteria.
• Implement robust monitoring systems for performance optimization.

Skills

Proficient in Google Cloud Platform

Deploying and optimizing LLMs

Experience with agentic architectures

NLP knowledge

Containerization

Scripting and automation skills

Tools

Google Cloud Platform

Docker

Kubernetes

Grafana

Job description

Job Description

Are You Ready to Make It Happen at Mondelēz International?

Join our Mission to Lead the Future of Snacking. Make It Uniquely Yours.

Mondelēz Consumer Solutions Global MDS (IT) Team is seeking an experienced candidate with strong AI infrastructure skills to join us during an exciting transformation. The GenAI Ops Engineer will be responsible for ensuring the reliable and efficient operation of Generative AI pipelines that power our Marketing Creative Agentic platform.

This role requires hands-on technical expertise and managing the end-to-end lifecycle of GenAI models (text, image, and future video), focusing on scalability, performance, and cost-effectiveness. The engineer will also shape the future of agentic architectures, working with frameworks such as Google’s Agent2Agent (ADK) and LangGraph, to develop more intelligent, modular, and autonomous capabilities.

The GenAI Ops Tech Engineer will collaborate with internal and external teams, technology partners, and business stakeholders. A strong foundation in AI, ML, and Cloud technologies is essential for guiding platform operations and future innovations.

How you will contribute

Key Responsibilities:

• Deploy, monitor, and maintain generative models in production, ensuring high availability and optimal performance.
• Evaluate and compare GenAI models based on accuracy, latency, cost, and relevance.
• Apply optimization techniques like fine-tuning, quantization, and pruning to enhance models.
• Design and optimize generative AI models for various applications, evolving the platform with newer frameworks and models.
• Manage infrastructure supporting GenAI workloads on GCP, including compute, networking, and storage.
• Implement monitoring and alerting systems to address performance issues.
• Optimize resource utilization and minimize operational costs.
• Support integration of agentic workflows using frameworks such as LangGraph and A2A, deploying them into production.
• Collaborate with data scientists, ML engineers, and platform teams for seamless delivery.
• Implement security best practices to protect infrastructure and data, ensuring compliance.
• Respond to operational issues with troubleshooting and resolution.
• Stay informed on GenAI advancements and identify opportunities for innovation.
• Guide technology selections through interactions with architecture, application, and technical teams.

What you will bring

Required Skills:

• Proficiency in GCP services such as Vertex AI, BigQuery, GKE, Cloud Run, and Cloud Functions.
• Experience deploying and optimizing LLMs, image generation models, or other GenAI models in cloud environments.
• Knowledge of evolving technologies like MCP and A2A, and their application in business and marketing.
• Ability to design scalable AI infrastructure and application stacks for ML operations.
• Familiarity with agentic architectures like LangGraph and A2A frameworks.
• Understanding of RAG models, knowledge retrieval, and their training processes.
• Experience with NLP, computer vision, and multimodal AI models.
• Techniques such as quantization, pruning, and distillation for model optimization.
• Knowledge of ML frameworks like Transformers, PyTorch, or TensorFlow.
• Proficiency in containerization (Docker, Kubernetes) and orchestration tools.
• Experience with monitoring and logging solutions, including Prometheus, Grafana, ELK, and cloud-native tools.
• Strong scripting skills in Python and Bash.
• Understanding of security best practices for cloud and AI infrastructure.
• Excellent communication skills for articulating technical strategies.
• Commitment to learning and professional growth.

Note: No relocation support available.

Business Unit Summary

At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. We deliver high-quality snacks globally, including brands like Oreo, Cadbury, Sour Patch Kids, and Trident. With over 80,000 employees in more than 80 countries, we are committed to diversity, growth, and sustainability.

We are an equal opportunity employer, considering all qualified applicants regardless of race, color, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.

Job Type: Regular Software & Applications, Technology & Digital