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Senior Machine Learning Scientist11105 Expedia, Inc. • Seattle, Washington, United States
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Senior Machine Learning Scientist

11105 Expedia, Inc.
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

Senior Machine Learning Scientist Responsibilities
Design and implement end‑to‑end ML solutions for medium‑to‑large projects, including problem framing, ideation, research, prototyping, deployment, and post‑launch monitoring. Build robust, scalable ML systems (batch and/or streaming) in partnership with engineering, covering data pipelines, feature computation, and model serving. Translate ambiguous business problems into well‑defined ML problems with clear success metrics and validation strategies. Develop, evaluate, and iterate on supervised, unsupervised, and deep learning models for prediction, recommendation, and optimization. Apply causal inference and experimental design (A/B testing) to accurately measure impact and guide decision‑making. Read and apply relevant academic and industry research to improve model architectures, training strategies, and evaluation methods. Contribute to defining best practices for experimentation and modeling within the team and help raise the technical bar for ML development. Build and iterate on models and applications leveraging GenAI/LLM technologies for customer support, content generation, and workflow automation. Use prompting, retrieval‑augmented generation, and tool/function‑calling patterns to integrate LLMs into production systems. Explore and prototype advanced ML techniques (e.g., reinforcement learning, sequence modeling, transformers) where they can provide clear business value. Design end‑to‑end modeling approaches, including data selection, feature engineering, algorithm choice, training procedures, and evaluation. Apply statistical rigor in analyzing experiments and observational data; quantify uncertainty, trade‑offs, and model risk. Define and monitor offline and online metrics that faithfully reflect business goals (e.g., customer satisfaction, cost‑to‑serve, operational efficiency). Partner closely with product managers, engineers, analysts, and operations to understand requirements, define roadmaps, and align on priorities. Communicate complex technical concepts in a clear, concise way to technical and non‑technical stakeholders. Build intuitive dashboards and visualizations to explain model behavior, experiment results, and business impact. Lead cross‑functional projects involving multiple partners, managing scope, timelines, and communication, and proactively surfacing risks and trade‑offs. Mentor junior scientists and engineers on modeling approaches, experimentation, and analytical problem solving.
Qualifications
PhD in a quantitative field (Computer Science, Statistics, Mathematics, Physics, Economics, Operations Research) with ~3+ years industry experience; OR Master’s degree with ~5+ years relevant industry experience. Proven track record of building and deploying ML models that meaningfully impact business metrics in a production environment. Strong knowledge of machine learning theory and practice, including supervised learning, representation learning, ranking/recommendation, and deep learning. Solid grounding in statistics, experimental design (A/B testing), and basic causal inference; comfortable designing and analyzing online experiments. Hands‑on experience with GenAI/LLM APIs (OpenAI, Hugging Face, Anthropic, Gemini) in prototypes or production. Proficiency in Python (pandas, scikit‑learn, PyTorch/TensorFlow, PySpark), SQL, and cloud‑based data/compute platforms (Spark, Airflow, feature stores, model serving frameworks). First‑principles problem solver with excellent written and verbal communication skills. Experience mentoring other scientists or engineers and contributing to technical culture is highly desirable.
Desired Experience
Domain experience in customer service, recommendations, personalization, or e‑commerce applications. Experience building ML systems for operational decision‑making (e.g., contact routing, triage, capacity/effort prediction, workflow optimization). Experience with reinforcement learning, bandits, or other advanced ML techniques. Experience leading and managing cross‑functional projects with measurable impact.
Compensation Seattle: $173,000.00 – $242,500.00 (potential up to $277,000.00). San Jose: $187,000.00 – $261,500.00 (potential up to $299,000.00). Starting pay varies with location, budget, and individual experience. Benefits Medical/dental/vision, paid time off, Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent (IATAN) membership. Equal Opportunity Statement Expedia Group 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, veteran status, or any other characteristic protected by law. This employer participates in E‑Verify. #J-18808-Ljbffr
  • Seattle, Washington, United States

Sprachkenntnisse

  • English
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