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PowerToFly

Principal Machine Learning Scientist - Principal Machine Learning Scientist – Ge

PowerToFly, Seattle, Washington, us, 98127

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Position Overview Expedia Group’s Machine Learning and Data Science team is looking to hire researchers and data scientists who are passionate about using machine learning to improve customer experience. You will develop state‑of‑the‑art algorithms and generative AI solutions to power and enhance post‑booking recommendations, customer service, and trip‑management use cases. The role focuses on tackling substantial technical challenges, from inference problems in long‑tail traveler data to multi‑objective optimization in dynamic, operationally complex environments.

Responsibilities Machine Learning Engineering

Configure, maintain, and optimize storage and processing environments (cloud, on‑premises, cluster management, etc.).

Build production‑grade data and machine learning pipelines that support batch and streaming applications.

Advocate for software design best practices and construct robust data and machine learning pipelines.

Machine Learning / Data Science

Perform applied research to consistently achieve desired solution performance and improve organizational capabilities.

Demonstrate an in‑depth understanding of all aspects of learning theory.

Support leaders in setting up frameworks for the machine learning development lifecycle and devise strategy.

Advise business leaders to create and enable robust ML solutions with high impact at an expert level.

Lead and mentor others in all machine learning activities.

Generative AI

Deep expertise in LLM fine‑tuning and prompt engineering (e.g., OpenAI APIs, Hugging Face, Anthropic Claude, Google Gemini).

Strong experience with AI orchestration tools (e.g., LangChain, LlamaIndex, vector databases for retrieval augmentation).

Hands‑on knowledge of function calling and API‑based reasoning models.

Proficiency in Python and AI development frameworks for building scalable AI applications.

Understanding of multi‑agent architectures and best practices in agentic AI design.

Experience with real‑world AI evaluation techniques, including golden sets, synthetic data generation, and interactive testing.

Statistics & Model Design

Leverage a solid theoretical foundation and apply advanced statistical methods to a broad range of problems.

Advanced experimental design (e.g., adaptive designs). Read relevant publications and implement described methods in business context.

Design end‑to‑end models based on detailed business requirements, selecting algorithms and data sources.

Ensure model output reflects deep business understanding, adhering to standard methodologies and the latest research.

Demonstrate critical understanding of business processes and recommend solutions that meet unique business needs.

Visualization, Communication & Stakeholder Management

Embed visualizations from tools, demonstrate proficiency in visualization tools, and apply data‑visualization principles consistently.

Create complex charts, use color palettes, typography, and UX considerations to present clear visualizations.

Be a persuasive storyteller, build trust with teams and partners, and influence across the organization.

Mentor and train others on analytical problem‑solving, project management, and influencing for business impact.

Manage stakeholders through frequent communication, expectation management, and timely delivery.

Minimum Qualifications

Bachelor’s, Master’s, or Ph.D. in a technical field or equivalent experience.

Expertise in at least two major ML programming languages (Python, R, Scala, etc.) and familiarity with others.

Experience leading large data science technical programs, delivering successful outcomes with cross‑functional teams of 10+.

Demonstrated contributions to the data science community through blog posts, talks, conferences, or similar.

Experience defining data science best practices at a team/capability level.

Expertise in configuring, maintaining, and optimizing storage and processing environments.

In‑depth understanding of all aspects of machine learning theory and practice.

Strong background in applying advanced statistical methods, including stochastic processes, Bayesian neural networks, Markov models, discriminant and factor analysis.

Continuous learning mindset to stay ahead of evolving technologies and techniques.

Strong communication and storytelling skills to convey complex technical concepts to diverse stakeholders.

Collaborative mindset and ability to lead cross‑functional teams to deliver innovative solutions.

Strategic thinking and business acumen to align ML initiatives with organizational goals.

Commitment to ethical and responsible AI practices to ensure fairness, transparency, and accountability.

Preferred Qualifications

Advanced experimental design experience (e.g., adaptive designs).

Expert knowledge of HTML/CSS/JavaScript.

Strong knowledge of charting packages and libraries.

Compensation The total cash range for this position in Seattle is $224,000.00 to $313,500.00. Employees may increase their pay up to $358,500.00 based on performance.

Starting pay will vary based on location, budget, and individual knowledge, skills, and experience. Pay ranges may be modified in the future.

Benefits We offer a full benefits package, including medical/dental/vision, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and an International Airlines Travel Agent membership.

View our full list of benefits.

Accommodations If you need assistance with any part of the application or recruiting process due to a disability or other physical or mental health condition, please reach out to our Recruiting Accommodations Team through the Accommodation Request.

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, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E‑Verify.

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