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Machine Learning Scientist IIIPowerToFly • San Jose, Arizona, United States
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Machine Learning Scientist III

PowerToFly
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
Jetzt Bewerben

Über

Responsibilities
Design & Implement ML Solutions: Take ownership of the end-to‑end ML lifecycle for your projects, from ideation and research to deployment and monitoring.
Test, Learn, and Iterate: Design and analyze tests to validate your models, quantify their business impact, and design future iterations.
Collaborate and Communicate: Partner closely with product managers, engineers, and business stakeholders to understand requirements, define problems, and communicate your findings and results effectively.
Qualifications Experience & Education
PhD or MS in a quantitative field (e.g., Computer Science, Economics, Statistics, Physics).
3+ years of hands‑on industry experience building and deploying machine learning models to solve real‑world problems.
Functional & Technical Skills
Expertise in applied ML: deep practical knowledge of machine learning theory (supervised/unsupervised learning, deep learning) and statistical modeling, strong command of experimental design (A/B testing) and causal inference to accurately measure impact.
Ability to design end‑to‑end ML solutions: framing the problem, choosing data sources, selecting algorithms, and defining evaluation strategy.
Experience with the ML software development lifecycle, including experimentation, deployment, monitoring, and iteration in production.
Strong programming skills in at least one major ML language (e.g., Python, Scala, Java) plus SQL; writes clean, modular, maintainable code.
Technical fluency: Strong programming skills in Python and its data science ecosystem (pandas, scikit‑lean, pySpark), plus proficiency in SQL.
First‑principles problem solver: Skilled at dissecting ambiguous problems and clearly communicating complex technical ideas.
Highly Desired Experience
Domain knowledge in customer service, recommendation systems, operational applications of ML, and/or e‑commerce.
Experience with reinforcement learning or other advanced ML techniques is a plus.
Experience building and deploying models using GenAI/LLM technologies.
Experience translating research and academic papers into improved model designs and techniques.
Minimum Qualifications
Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
5+ years of relevant professional experience.
Proven ability to design end‑to‑end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring.
Strong programming skills in Python and its data science ecosystem (such as pandas, scikit‑learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases.
Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring.
Preferred Qualifications
MS or PhD in a quantitative field such as Computer Science, Economics, Statistics, Physics, or a related discipline.
3+ years of hands‑on industry experience building, deploying, and iterating on machine learning models that solve real‑world problems in production environments.
Proven ability to design end‑to‑end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring.
Strong programming skills in Python and its data science ecosystem (such as pandas, scikit‑learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases.
Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring.
Pay Range (Seattle) The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Pay Range (San Jose) The total cash range for this position in San Jose is $149,000.00 to $208,500.00. Employees in this role have the potential to increase their pay up to $238,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
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. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I‑9 to confirm work authorization.
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  • San Jose, Arizona, United States

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  • English
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