Top Machine Learning Jobs in Seattle, WA
Seeking a Machine Learning Architect to elevate the Machine Learning and Artificial Intelligence R&D strategy at Qualtrics. Responsibilities include designing robust AI architectures, selecting appropriate AI technologies, collaborating with cross-functional teams, and optimizing ML systems for performance and scalability.
Seeking a Principal Data Scientist with strong engineering skills to lead ML and AI initiatives across multiple teams at a financial services company. Responsibilities include building ML / AI products, setting technical standards, providing mentorship, and collaborating with various departments. Requires strong experience in machine learning, AI, data products, and software engineering. Must have expertise in technologies like Airflow, DBT, Git, Docker, Kubernetes, BI tools, Spark, AWS, Snowflake, Scikit-learn, TensorFlow, PyTorch.
Build and deploy ML models for identity resolution and ads attribution. Collaborate with cross-functional teams to align on ML strategies. Stay updated with the latest ML technology and solve complex problems. Ensure code quality and build scalable products.
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Join the Chewy Search & Recommendations team as a Principal Machine Learning Engineer/Data Scientist. Develop models to simplify product discovery for pet lovers on Chewy.com. Work on all stages of model development and impact millions of customers daily.
Quality Engineering role working on Machine Learning technologies at ServiceNow. Responsible for test automation, testing AI/ML models, creating test plans, and supporting engineering organizations. Requires Bachelor's or Master's in Computer Science/Engineering with 3 years of experience.
Senior Machine Learning Software Engineer at Dropbox, responsible for designing, building, evaluating, and deploying large-scale ML systems. Collaborate with cross-functional teams to personalize user experiences and drive impactful outcomes. Requires strong industry experience and software engineering skills in Python, Go, and C/C++.
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Lead a team of Machine Learning Engineers and Data Scientists to build machine learning solutions for fraud prevention in the financial services industry. Partner with ML ops and ML platform teams to improve research efficiency and model quality. Define frameworks for evaluating model performance and accelerate the model development processes. Evaluate and introduce new algorithms and model architectures to improve performance.
Develop advanced algorithms, execute statistical and data mining techniques, evaluate emerging datasets and technologies, contribute to thought leadership, possess strong communication and problem-solving skills.
Drive product impact via data and evaluation for products and services used by millions globally. Partner with Search engineering teams to improve search quality and guide feature development using data. Research and develop evaluation methods to enhance Siri's user-facing products. Work with large, complex datasets and build analysis pipelines iteratively.
Conduct foundational research into solutions for analyzing data using natural language and integrating them into products. Develop and deploy AI models, implement ML infrastructure, and contribute to AI community through research and open-source projects.
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