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Machine Learning Engineer II
Machine Learning Engineer IIExpedia Group • HomeAway, Austin Domain 11
Machine Learning Engineer II

Machine Learning Engineer II

Expedia Group • HomeAway, Austin Domain 11
[job_card.30_days_ago]
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  • [job_card.full_time]
[job_card.job_description]

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.

This work directly aligns with Expedia Group’s strategic priorities and core principles—delivering exceptional traveler experiences and making travel more accessible and rewarding for people around the world.

We are seeking a dynamic and highly motivated Machine Learning Engineer III to help us meet our goals of leading the development of ML-powered features that enhance the traveler experience across Expedia Group brands by working closely with cross-functional teams to design and scale systems for Ranking, Recommendations, Pricing, and Search. This includes rapid prototyping of innovative ideas, contributing to all phases of the ML lifecycle, and integrating generative AI into production workflows. Team members are expected to bring strong technical judgment to system design and actively shape the team's technical direction.

In this role, you will :

System & Software Design : Designs and develops moderately complex, testable, and observable systems; contributes to architectural discussions, especially for big data and ML applications.

API & Service Development : Builds APIs and services for use across business units, ensuring reusability and scalability.

Business Impact Alignment : Understands how technical work supports business goals; identifies and solves project-level business problems with minimal guidance.

Cross-Functional Collaboration : Coordinates with stakeholders across engineering, product, and data to align priorities and deliver shared solutions.

Innovation & Optimization : Identifies inefficiencies in code and systems; proposes improvements and innovations in ML engineering, platforms, and tooling.

Operational Excellence : Ensures performance, scalability, and reliability of systems through monitoring, testing, and adherence to SLAs.

Mentorship & Code Quality : Leads code reviews, mentors peers, and contributes to a culture of engineering excellence and best practices.

Technical Communication : Documents and presents findings (e.g., RCAs or tech deep dives) clearly to both technical and non-technical audiences.

Strategic Thinking : Applies systems thinking to identify process or policy improvements that scale beyond immediate teams or projects.

Community Engagement : Participates in communities of practice, promotes shared learning, and fosters a culture of knowledge exchange.

Experience and qualifications :

Bachelor’s or Master’s degree in Computer Science, Statistics, Math, Engineering, or related technical field; or equivalent related professional experience.

2+ years of experience in software engineering or machine learning engineering with a Master's degree and 3+ years of experience in software engineering or machine learning engineering with a Bachelor's degree

Programming Proficiency : Comfortable programming in Python and Experience developing software in at least 3 languages, with a strong command of at least one language across multiple tech stacks; able to choose the right language for the task.

Machine Learning Engineering : Built and maintained at least one end-to-end ML pipeline in production, covering feature engineering, model training, validation, and scalable inference.

ML Libraries & Frameworks : Proficient in PyTorch, TensorFlow, and common patterns for model serving; familiar with dependency management in ML / DS systems.

Big Data & Distributed Systems : Strong command of Spark (including map-reduce); experience training ML models on large datasets with GPUs or distributed compute.

Cloud & Infrastructure : Experience of using cloud services (e.g. AWS). Experience with workflow orchestration tools (e.g. Airflow). Experience building streaming applications in cloud / hybrid environments; familiar with IAM policies and cloud storage (e.g., S3).

Software Engineering Principles : Applies data structures, design patterns, and software frameworks to write clean, modular, maintainable code.

Testing & Debugging : Designs testable systems, uses tools to monitor / debug code, and fixes issues within SLA constraints.

Continuous Learning & Technical Breadth : Stays current with emerging technologies, seeks new skills, and shares knowledge across teams.

The total cash range for this position in Austin is $112,000.00 to $157,000.00. Employees in this role have the potential to increase their pay up to $179,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

The total cash range for this position in Seattle is $112,000.00 to $156,500.00. Employees in this role have the potential to increase their pay up to $179,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

The total cash range for this position in Austin is $112,000.00 to $156,500.00. Employees in this role have the potential to increase their pay up to $179,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

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 .

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 is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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Machine Learning Engineer • HomeAway, Austin Domain 11

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