Top Remote Machine Learning Jobs in Seattle, WA
Senior Machine Learning Engineer role at Square focusing on developing cutting-edge ML models and algorithms for company-wide metrics and GTM channel attribution. Responsibilities include building data science and ML solutions, partnering with stakeholders, and staying updated on advancements in the field.
Seeking a Senior Machine Learning Engineer with expertise in data-driven attribution to join the Measurement Machine Learning teams at Square. Responsibilities include building ML solutions, partnering with stakeholders for growth strategy, and staying updated on industry trends.
The Staff Machine Learning Engineer at Cruise will drive the robotics aspects of the Simulation Smart Agents software stack, collaborating with specialists to deploy algorithms and ML models, optimize ML pipelines, create data pipelines, define metrics for evaluation, and accelerate engineer velocity within Simulation. The role requires expertise in robotics, machine learning, ML frameworks, runtime optimization, and programming skills in C++ or Python.
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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.
Build AI and Machine Learning solutions to transform user experience and workflow efficiency of enterprise services. Collaborate with a team to produce quality software using advanced technologies. Ensure scalability and performance across multiple languages.
Design, build, and manage distributed services and pipelines for Underwriting & Credit at Cash App. Lead multi-person projects, ensure high code quality, collaborate with various teams, and contribute to the growth of development capabilities. Remote work with a distributed team in the USA and Canada.
As a Machine Learning Engineer, you will analyze opportunities, propose ideas, train and evaluate ML models, run experiments, and deploy solutions to production. You will contribute to ML architecture and be part of the ML community at Stripe. Responsibilities include improving performance, evaluating systems, and ensuring model quality. Minimum requirements include 5 years of end-to-end ML development experience, an advanced degree in a quantitative field, and proficiency in Python, Scala, and Spark.
Specialist Solutions Architect role focused on architecting production-grade ML applications on Databricks, optimizing ML workloads, collaborating with product teams, and serving as a technical advisor for GenAI solutions.
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