Senior Machine Learning Engineer

Introduction to the Team:

Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.

We are seeking a Senior Machine Learning Engineer to join our Universal Messaging Platform team. In this role, you will play a key part in shaping the future of CRM Personalization—transforming how we engage travelers across marketing channels such as email, push, SMS, and WhatsApp.

In this role, you will:

• Collaborate closely with ML Scientists to productize and scale ML models, from experimentation to robust production systems

• Design, build, and own large-scale, distributed machine learning systems for training, deployment, inference, and monitoring

• Lead design discussions and architecture reviews; drive high-impact engineering decisions for ML platforms and applications

• Mentor and coach junior engineers and peers on best practices in ML engineering, system design, and code quality

• Develop and maintain reusable components, libraries, and tools to accelerate ML development lifecycle

• Proactively identify areas for improvement in model performance, pipeline efficiency, data quality, or platform capabilities

• Ensure scalability, observability, and fault-tolerance across all components of the ML stack

• Promote engineering excellence by advocating for best practices in testing, CI/CD, infrastructure-as-code, and monitoring

• Partner with stakeholders across Data Engineering, Product, Marketing, and Platform teams to align solutions with business goals

• Stay up to date on advancements in MLOps, ML frameworks, distributed systems, and apply learnings to improve systems and processes

Minimum Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

• 8+ years of experience in software/ML engineering with a proven track record of delivering ML solutions at scale

• Strong programming skills in modern languages such as Python, Scala, or Java.

• Deep experience in building and maintaining production-grade ML pipelines and infrastructure

• Expertise in MLOps practices, including model lifecycle management, versioning, monitoring, and CI/CD for ML

• Experience with big data ecosystems (e.g., Spark, Hive, Databricks, Delta Lake) and streaming technologies

• Proficient in working with ML frameworks like TensorFlow, PyTorch, XGBoost, or similar

• Experience working in cloud-based environments (AWS, GCP, or Azure) and with infrastructure-as-code tools

• Hands-on experience with orchestration tools like Flyte, Airflow, Kubeflow, etc.

• Proficient in containerization and orchestration technologies like Docker and Kubernetes

• Collaborative, curious, and eager to explore new paradigms in AI

• Passion for mentoring, continuous learning, and contributing to a high-performance engineering culture

• Demonstrated ability to lead cross-functional projects and influence technical direction across teams

• Experience with automated testing across different layers (unit, integration, functional)

• Familiarity with advanced ML techniques, including deep learning, NLP, recommendation systems, and generative AI

• Experience designing or implementing multi-agent architectures for autonomous collaboration and decision-making

• Understanding of agent planning, memory, tool use, and self-reflection mechanisms