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Top Machine Learning Jobs in Seattle, WA
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
The Senior Machine Learning Engineering Manager will oversee the end-to-end machine learning lifecycle, manage core service development, mentor team members, and collaborate with product managers and various teams to enhance AI/ML modeling solutions for business applications.
Top Skills:
Agile DevelopmentAIData ScienceMachine LearningOperations ResearchPythonSQLStatistics
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
The Machine Learning Engineer will build and monitor model pipelines, scale ML algorithms for large datasets, enhance ML engineering platforms, implement MLOps, and collaborate with teams to deliver projects efficiently. Responsibilities include writing production-ready code, performing design/code reviews, and researching new architecture patterns.
AdTech • Digital Media • News + Entertainment
In this role, you will develop and maintain machine learning algorithms for personalization on Hulu's platforms. You'll work with engineering and product teams to optimize processes and explore innovative methods for recommendations. Your responsibilities include algorithm development, feature engineering, maintaining deployment standards, and collaborating on new personalization opportunities.
Featured Jobs
Artificial Intelligence • Information Technology • Natural Language Processing • Software • Business Intelligence • Generative AI
The Machine Learning Engineer II at Qualtrics will focus on enhancing customer care through machine learning and AI, developing and optimizing machine learning models, creating scalable data pipelines, and collaborating with cross-functional teams to solve complex customer problems.
Top Skills:
Artificial IntelligenceC#Data PipelinesJavaMachine LearningMicroservicesPythonPyTorchTensorFlow
eCommerce • Healthtech • Pet • Retail • Pharmaceutical
As a Machine Learning Engineer III, you will lead the development of machine learning solutions for Chewy’s new Sponsored Advertising team. Your role includes deploying models for product ranking and auction algorithms, collaborating with product leaders, mentoring junior scientists, and communicating findings to senior leadership while establishing high performance standards for models.
Fintech • HR Tech
The Senior Machine Learning Engineer will build and deploy machine learning models to mitigate risks in payments, collaborate with cross-functional teams, develop scalable frameworks, and effectively communicate results to stakeholders.
Artificial Intelligence • Digital Media • eCommerce • Marketing Tech • Software
The Staff Machine Learning Engineer will collaborate with product managers and engineers to design and productionize machine learning models, improve service performance, and maintain a high-quality codebase. Responsibilities include building machine learning solutions, conducting experiments, and sharing knowledge within the team.
Top Skills:
Feature StoreGoJavaKubeflowKubernetesPythonTfx
eCommerce • Fintech • Payments • Software • Financial Services
The Machine Learning Engineer II role at Remitly involves developing machine learning models for fraud prevention in financial services. The engineer will build models for transaction risk assessment, collaborate with infrastructure teams to meet performance requirements, and work on implementing new features collaboratively with scoring engineers.
Top Skills:
MatplotlibNumpyPandasPythonScikit-LearnScipySparkSQL
Fintech • Software • Financial Services
The Senior Machine Learning Engineer will design and maintain ML infrastructure, develop and deploy machine learning models, monitor performance, collaborate with teams, and mentor junior engineers at Kikoff, a consumer fintech startup focused on credit-building solutions.
Fintech • Healthtech • Software
The Data Scientist III (ML Engineering) will develop and optimize machine learning solutions to improve Cedar’s healthcare platform. Responsibilities include deep data analysis, building pipelines, collaborating with engineering teams, and evaluating model performance to enhance patient experiences.
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