Machine Learning Scientist II

About the role

We are looking for a hands-on Machine Learning Scientist who is passionate about applying machine learning to complex prediction and optimization problems that drive an ecosystem anticipating traveler needs, personalizing dynamic add-ons and upsells, and improving service experiences. This role focuses on developing state-of-the-art machine learning algorithms to enhance customer experience across post-booking recommendations, customer service, and trip management use cases. You will tackle technical challenges such as inference problems from long-tail traveler data and multi-objective optimization in dynamic, operationally complex environments.

Responsibilities

• Design and implement end-to-end machine learning solutions, from ideation and research to deployment and monitoring.
• Take ownership of the ML lifecycle, including problem formulation, data preparation, algorithm selection, feature engineering, evaluation, and production deployment.
• Design and analyze tests to validate models, quantify business impact, and iterate on future improvements.
• Collaborate with product managers, engineers, and business stakeholders to understand requirements, define problems, and communicate findings effectively.
• Apply machine learning to complex prediction and optimization problems in post-booking recommendations, customer service, and trip management.

Requirements

• Bachelor’s degree in Computer Science or a related technical field, or equivalent professional experience.
• 1+ years of relevant professional experience in machine learning or data science.
• Proven ability to design end-to-end ML solutions, including problem formulation, data preparation, algorithm selection, feature engineering, evaluation, and deployment.
• Strong programming skills in Python and its data science ecosystem (e.g., pandas, scikit-learn, PySpark) and proficiency in SQL.
• Experience following software engineering best practices and contributing to shared codebases.
• Familiarity with AI-driven systems, tools, or workflows, including the machine learning software development lifecycle from experimentation to operational monitoring.

Skills

• Expertise in applied ML: Deep, practical knowledge of machine learning theory (supervised/unsupervised learning, deep learning) and statistical modeling.
• Experimental design: Strong command of A/B testing and causal inference to measure impact accurately.
• Technical fluency: Strong programming skills in Python (or Scala/Java) and SQL; writes clean, modular, maintainable code.
• First-principles problem solver: Skilled at dissecting ambiguous problems and communicating complex technical ideas clearly.

Preferred Qualifications

• MS or PhD in a quantitative field such as Computer Science, Economics, Statistics, Physics, or a related discipline.
• 2+ years of hands-on industry experience building, deploying, and iterating on machine learning models in production environments.
• Domain knowledge in customer service, recommendation systems, operational applications of ML, or e-commerce.
• Experience with reinforcement learning or other advanced ML techniques.
• Experience building and deploying models using GenAI/LLM technologies.
• Experience translating research and academic papers into improved model designs and techniques.

Pay

The total cash range for this position in Seattle is $112,000 to $156,500, with potential to increase up to $179,000 based on performance. In San Jose, the range is $122,500 to $171,500, with potential to increase up to $196,000. Starting pay varies based on location, available budget, and individual qualifications.

Benefits

• Medical, dental, and vision coverage.
• Paid time off.
• Employee Assistance Program.
• Wellness and travel reimbursement.
• Travel discounts.
• International Airlines Travel Agent Network (IATAN) membership.