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Sr. Machine Learning Engineer - Advertising TechnologyExpedia , Inc. • San Jose, Arizona, United States
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Sr. Machine Learning Engineer - Advertising Technology

Expedia , Inc.
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
Jetzt Bewerben

Über

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. Senior Machine Learning Engineer Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. We are seeking a Senior Machine Learning Engineer to join our high-performing Advertising Technology team, where we build and operate large-scale batch and real-time ML systems that power pricing, inventory optimization, ranking, and trust & safety across the ad platform. This role sits at the intersection of machine learning, distributed systems, and MLOps, directly influencing how models are designed, deployed, and operated in production at scale. You will work closely with Software Engineering, Data Science, Product, and Platform teams to translate modeling ideas into reliable, observable, and scalable ML systems, while setting technical direction, raising engineering standards, and mentoring others as the platform and business grow. In this role, you will:
Collaborate with Software Engineers and ML Engineers/Scientists to design and build large-scale batch and real-time ML systems for advertising use cases Propose, lead, and deliver high-impact ML applications across pricing, inventory, content, and trust & safety, aligning technical decisions with business outcomes Own the end-to-end lifecycle of mid- to large-scale ML projects, from system design and model development through deployment and production operations Establish and promote ML engineering best practices, including model quality, MLOps, observability, and scalable system design Mentor junior engineers and support teams in integrating ML into existing production systems Partner with senior stakeholders across organizations to drive shared standards, communities of practice, and cross-team learning Lead complex, cross-organizational initiatives to improve performance, reliability, and scalability of ML systems
Minimum Qualifications
8+ years (BS) / 6+ years (MS) of industry experience building and deploying machine learning models in production Strong experience with distributed data processing and large-scale datasets (Spark preferred) Proven ability to design, deploy, and operate real-time or near–real-time ML systems end to end, including feature pipelines, model training and validation, scalable inference, monitoring, drift detection, and retraining Proficiency in Python with ML frameworks such as PyTorch or TensorFlow, and strong working knowledge of Scala or Java Deep expertise in end-to-end MLOps, including training and inference workflows, CI/CD for ML, model versioning, and automated retraining Strong ownership of ML observability, including model performance monitoring, data quality checks, drift detection, alerting, and root-cause analysis Experience operating cloud-native ML platforms and distributed systems (AWS, SageMaker, Kubernetes, Spark, Databricks) with reliability, scalability, and cost awareness
Preferred Qualifications
Proven experience building and scaling production ML and AI systems, including LLMs, RAG pipelines, embeddings, and retrieval-based architectures Strong foundation in machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, bias/variance tradeoffs, and offline vs online metrics Hands-on experience designing, training, tuning, and deploying ranking, prediction, classification, recommendation, forecasting, or NLP models Background in ads, marketplaces, e-commerce, or travel platforms is a plus
The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, 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 San Jose is $199,000.00 to $278,500.00. Employees in this role have the potential to increase their pay up to $318,500.00, 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. Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness and travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. 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. Expedia Group is an inclusive employer. We provide equal opportunity for all qualified applicants and do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We participate in E-Verify where applicable. 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. CST: 2029030-50 #J-18808-Ljbffr
  • San Jose, Arizona, United States

Sprachkenntnisse

  • English
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