Software Development Engineer II

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you’ll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Software Development Engineer II, ML Systems — Marketing (Meta/SEM Bidding)

Introduction to the team

We create and deliver an aligned, dedicated marketing strategy to fuel each Expedia Group brand’s success. Since our travelers interact with us through our brands, we have a brand focus in our marketing, while leveraging the scale and efficiency we’ve built in functional expertise.

The Meta/SEM Bidding Programs team builds and operates the high-scale data and machine learning systems that power our bidding programs. We are looking for a Software Development Engineer II who writes clean, reliable, production-grade software and partners closely with machine learning engineers to build the pipelines, services, and platform that bring ML models to life in production.

In this role, you will

• Implement and enhance well-scoped software and data components within complex, business-critical services — from design input through coding, testing, deployment, and production support, with guidance on larger decisions.
• Build and maintain the data pipelines, services, and infrastructure that support model training, evaluation, and serving, working alongside ML engineers to turn experimental workflows into robust production systems.
• Contribute to batch and streaming (online) data and inference workflows, learning how models are trained, served, and monitored at scale.
• Instrument systems and pipelines to capture operational and quality metrics (latency, throughput, errors, and key business signals), and help diagnose and resolve production issues.
• Participate in code reviews, on-call rotations, and incident response, taking ownership of the reliability and observability of the components you build.
• Use AI as a co-pilot across the software development lifecycle — to clarify requirements, generate and refine code, and strengthen automated tests — and apply generative AI/LLM techniques where they add value.

Experience and Qualifications

• Strong problem-solving skills — the ability to deeply understand a problem and reason clearly about the right approach — which we value above any single technology.
• 2+ years of relevant professional experience building and shipping production software, ideally including data-intensive or backend services in a cloud or hybrid environment.
• Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
• A strong command of Python, along with experience building APIs and services (FastAPI, REST).
• Solid software engineering fundamentals — data structures, algorithms, testing, and version control.
• Experience building, deploying, and supporting distributed systems and cloud services on AWS, including contributing to monitoring, alerting, and basic performance improvements.
• Experience running containerized and orchestrated workloads with Kubernetes at scale.
• Working knowledge of Go and Spark (Scala/PySpark) or similar big data frameworks, including basic evaluation, optimization, and debugging of large-scale data processing applications.
• Familiarity with a range of databases (e.g., Hive, Iceberg, Postgres) and workflow orchestration tools (e.g., Airflow, Flyte, Argo).
• Exposure to MLOps practices (CI/CD for ML, experiment tracking, model registry, deployment and monitoring tooling) and to machine learning concepts or ML pipelines — deep ML expertise is not required, but curiosity and a willingness to grow into data/ML engineering are important.
• Hands-on experience using AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code, or equivalent) in day-to-day work, consistent with Expedia Group’s expectation that engineers actively build and apply AI skills.

**Accommodation …