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Expedia Group
Expedia Group

Online travel company

Machine Learning Engineer III

직무머신러닝
경력미들급
위치UK - London
근무오피스 출근
고용정규직
게시1주 전
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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

B2B is the business-to-business arm of Expedia Group, bringing our travel technology and distribution capabilities to partners worldwide. Our partners include global financial institutions, corporate-managed travel programs, offline travel agencies, and major travel suppliers such as airlines and hotel chains.

The B2B Machine Learning Engineering team builds and operates the ML platforms and systems that power ranking, recommendations, and pricing optimization for our partners. We design, build, and maintain the infrastructure for deploying ML solutions, managing data pipelines, and optimizing compute resources so our models run efficiently and reliably at scale.

You will join the Revenue Optimization ML team within B2B. This is a high-impact engineering team that combines deep infrastructure expertise with applied ML knowledge to deliver measurable business value for our partners and for Expedia Group.

About the role

We are looking for a Machine Learning Engineer III (L) who is passionate about building robust, scalable ML systems. In this role, you will architect and implement end‑to‑end ML solutions: from data and training pipelines through deployment, serving, monitoring, and operations, with a strong focus on high-scale, high-throughput services.

This role blends software engineering, distributed systems, and MLOps. You will work closely with ML scientists to streamline the path from experimentation to production and to continuously improve the performance, scalability, and reliability of our ML stack.

While this is primarily an individual contributor role, you will also mentor junior engineers and help set technical direction for the team.

We welcome strong, language‑agnostic problem solvers who are excited to grow with us—even if you do not meet every single requirement listed below.

What you will do

  • Design and implement scalable ML infrastructure for model training, deployment, and serving across both batch and real‑time use cases.
  • Build and maintain data pipelines for large‑scale data processing, feature engineering, and training data generation.
  • Optimize compute and model serving performance, focusing on low‑latency, high‑throughput, and cost‑efficient inference.
  • Implement monitoring, logging, and alerting for ML systems, and contribute to robust MLOps and CI/CD practices (e.g., automated model deployment and rollback).
  • Partner with ML scientists to streamline the model development–to–production workflow, including tooling, APIs, and best practices.
  • Research, evaluate, and integrate new technologies (frameworks, tools, platforms) that improve our ML infrastructure and developer productivity.
  • Provide technical mentorship to junior engineers and communicate complex technical topics clearly to diverse stakeholders across product, engineering, and data science.

Experience and qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field (or equivalent practical experience).

Experience:

  • 4+ years of experience in Software Engineering, Data Engineering, or Machine Learning Engineering roles (preferred).
  • Experience in at least one of: deploying models to production, managing training data pipelines, or optimizing compute for low‑latency inference.

Programming & ML:

  • Strong problem‑solving and software engineering skills.
  • Experience with ML frameworks such as Tensor Flow or Py Torch.
  • Understanding of ML algorithms, model architectures, and the practical considerations of building scalable, reliable ML systems.
  • Platforms & infrastructure:
  • Exposure to at least one major cloud platform (e.g., AWS).
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
  • Familiarity with scalable data systems such as Spark, Kafka, or equivalent technologies.
  • Familiarity with observability and reliability tooling (metrics, logging, tracing, dashboards, and alerting) to operate production ML systems effectively.
  • MLOps & collaboration:
  • Familiarity with CI/CD tools (e.g., GitHub Actions or similar).
  • Exposure to ML model serving and tracking tools.
  • Strong communication skills and ability to collaborate effectively with cross‑functional teams.

If you are excited about building robust ML systems, enjoy solving complex engineering problems, and want to help shape how Expedia Group leverages machine learning for our B2B partners, we’d love to hear from you.

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®, Cheap Tickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, Car Rentals.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.

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Expedia Group 소개

Expedia Group

Expedia Group, Inc. is an American travel technology company that owns and operates travel fare aggregators and travel metasearch engines, including Expedia, Hotels.com, Vrbo, Travelocity, Hotwire.com, Orbitz, Ebookers, CheapTickets, CarRentals.com, Expedia Cruises, Wotif, and Trivago.

10,001+

직원 수

Seattle

본사 위치

$6.8B

기업 가치

리뷰

10개 리뷰

3.8

10개 리뷰

워라밸

2.8

보상

3.7

문화

4.2

커리어

3.3

경영진

2.5

68%

지인 추천률

장점

Supportive team and colleagues

Flexible work arrangements and remote options

Interesting and creative projects

단점

Work-life balance challenges and long hours

High stress and burnout during peak seasons

Fast-paced and overwhelming environment

연봉 정보

1개 데이터

Intern

Intern · Machine Learning Scientist Intern

1개 리포트

-

총 연봉

기본급

-

주식

-

보너스

-

면접 후기

후기 6개

난이도

2.8

/ 5

소요 기간

14-28주

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Assessment/Coding Challenge

4

Final Interview

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit