Machine Learning Engineer III

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

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 maintain a brand-focused approach in our marketing while leveraging the scale and efficiency we’ve built through functional expertise.
The Meta/SEM Bidding Programs team at Expedia Group is looking for a Machine Learning Engineer III who mentors junior engineers, applies modern data and ML engineering principles to improve existing systems, and leads complex, well-defined projects in a high-scale production environment.

In this role, you will:

• Collaborate with peers and stakeholders across the organization to understand cross-dependencies, shape solutions, and translate experimental DS workflows into robust production pipelines.
• Develop, refactor, and test complex ML and software components, applying solid software engineering practices (design principles, data structures, design patterns) to produce clean, maintainable, and optimized code.
• Contribute to the design of big data and ML applications, including how models are trained, evaluated, and served at scale across batch and streaming (online) inference workflows.
• Evaluate, monitor, and operate ML models in production, instrumenting pipelines to capture online and offline metrics (latency, throughput, accuracy/quality, drift, and business KPIs) and using them to drive iteration.
• Diagnose model and pipeline issues (e.g., performance regressions, instability), distinguish data drift vs. model drift, and drive mitigations such as retraining, recalibration, and feature or architecture changes.
• Design and implement guardrails for production models (safety constraints, thresholds, fallbacks, safe defaults) to protect customer and business outcomes and improve reliability.
• Identify and address areas of inefficiency in code, model architectures, and system operations (including memory/compute efficiency), recommending and implementing improvements to observability, policies, and processes.

Who you are:

• 5+ years of relevant professional experience with end-to-end machine learning engineering pipelines in production (feature engineering, model training, validation, deployment, scoring, monitoring, and iteration), including streaming applications in hybrid/cloud environments.
• Bachelor’s or Master’s degree in a technical field (e.g., Computer Science) or equivalent relevant work experience.
• Strong command of Spark (or similar big data frameworks), including evaluating, optimizing, and debugging large-scale data processing applications.
• Proficiency with ML libraries such as PyTorch and/or TensorFlow, and experience integrating models into production services for inference at scale.
• Solid ML fundamentals with working knowledge of deep learning and big data concepts, and demonstrated experience refactoring and scaling ML models for production (latency, throughput, and memory footprint).
• Hands-on experience evaluating and monitoring ML models in production, including metric and alert design, feedback loops, and basic MLOps practices (CI/CD for ML, experiment tracking, model registry, deployment and observability tools).
• Familiarity with secure data access and governance (e.g., IAM policies for S3, access patterns for training and serving) and with designing moderately complex distributed systems centered on ML training and serving.

#LI-MF2

Accommodation requests

If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.

We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.

Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.