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

Traveltechessentialist
  • 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.
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 when one of us wins, we all win.
We provide a full benefits package, including travel perks, generous time‑off, parental leave, a flexible work model, and career development resources to fuel our employees’ passion for travel.
Senior Machine Learning Engineer Expedia Technology teams partner with Product to create innovative products, services, and tools that deliver high‑quality experiences for travelers, partners, and employees. A platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and satisfaction. We are building large‑scale batch and real‑time ML systems that power pricing, inventory optimization, ranking, and trust & safety across our ad platform.
Responsibilities
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.
Salary Range – Seattle: $184,500.00 to $258,000.00. Potential to increase salary to $295,000.00 based on performance. Seattle and San Jose ranges are provided separately.
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 anyone unless you’re confident in the recipient. 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 SSA and, if necessary, the DHS with information from each new employee’s I‑9 to confirm work authorization.
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  • San Jose, Arizona, United States

Sprachkenntnisse

  • English
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