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.

To shape the future of travel, people must come first. 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. Were building a more open world. Private Label Solutions (PLS) is the B2B arm of Expedia Group. These businesses include global financial institutions, corporate managed travel, offline travel agents, global travel suppliers (like major airlines) and many moreWe are looking for a Machine Learning Engineer II to join the Private Label Solutions (PLS) Machine Learning Engineering. You will join a team that builds and

maintains

the infrastructure for deploying ML solutions, managing data pipelines, and

optimizing

compute resources for our ranking problems, recommendation engines, and pricing optimization systems. Your work will contribute substantial value to our partners and EG by ensuring our ML models are efficiently deployed, scaled, and

monitored

in production environments.You will gain

expertise

in ML infrastructure, data engineering, cloud computing, and scalable system design while working closely with our ML scientists to bring their models to life in production.This role requires an individual with

a strong foundation

in software engineering and machine learning infrastructure, who is passionate about building robust and scalable systems. You should be comfortable with ambiguity, enjoy tackling complex technical challenges, and have a keen interest in

optimizing

ML workflows.We

welcome

candidates who are strong problem solvers and passionate about building ML systems

. Design and implement scalable infrastructure for deploying ML models in production.

- Build and

maintain

data pipelines for efficient processing and feature engineering.

- Optimize

compute resources and enhance model serving performance.

- Set up monitoring and logging systems for deployed ML models.

- Collaborate with ML scientists to streamline development-to-production workflows.

- Improve CI/CD processes, contribute to A/B testing frameworks, and uphold ML engineering best practices.

You hold a Bachelors or

Masters in Computer Science

, Software Engineering, or a related field.

- You have 2+ years of experience in Software, Data, or ML engineering roles (preferred).

- You bring strong problem-solving skills,

proficiency

in Python, and familiarity with ML frameworks like TensorFlow or

PyTorch

.

- AWS, GCP), containerization (Docker, Kubernetes), and scalable data systems (e.g., You are experienced or interested in ML model serving technologies (e.g.,

You understand ML algorithms and collaborate effectively with cross-functional teams through

strong communication

skills.

Accommodation requestsIf 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.Employment opportunities and job offers at Expedia Group will always come from Expedia Groups Talent Acquisition and hiring teams. The official website to find and apply for job openings at Expedia Group is

careers.All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.#