Top Machine Learning Jobs in Los Angeles, CA
ML Engineers at Disney are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney, Hulu and ESPN+
Design, build and enhance batch and real-time inference services and tooling to support ML use cases. Facilitate modelers by providing necessary infrastructure/tools. Partner with ML modelers to encourage adoption of new tools and technologies.
Design, implement, and scale critical machine learning components and services to support strategic initiatives at Snap Inc. Responsibilities include building a next-generation training framework, optimizing training performance, developing an AutoML platform, collaborating with teams, advocating for best practices, and providing technical direction.
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The Machine Learning Senior Engineer at ZS will be responsible for building, orchestrating, and monitoring model pipelines, scaling machine learning algorithms, and implementing ML Ops. They will collaborate with client teams and global development team to successfully deliver projects and contribute to researching and evaluating the latest architecture patterns and technologies.
Senior Machine Learning Software Engineer at Dropbox responsible for designing, building, evaluating, deploying, and iterating on large scale Machine Learning systems. Collaborate with cross-functional teams to personalize user experiences and contribute to technical strategy for machine learning lifecycle.
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Design and build machine learning models to solve classification, regression, and machine vision problems. Perform hyper-parameter tuning, implement production-ready pipelines, optimize prediction performance, and more.
Seeking a Senior Machine Learning Engineer to drive product strategy forward by leveraging in-house code and data frameworks, developing scalable algorithms, and collaborating with cross-functional teams to enhance ML systems.
Build cloud-based GenAI/ML solutions for enterprise services, oversee strategy for improvements, collaborate with a team of scientists and engineers, and drive data acquisition and evaluation metrics for software quality.
Designs, develops, and programs methods, processes, and systems to analyze and generate insights from big data sources. Works with product and service teams to identify questions and issues for data analysis. Develops software programs and algorithms to evaluate large datasets. Interprets and communicates insights and findings to managers.
As an ML Ops and Data Engineer, you will optimize the performance of our robotic systems by integrating machine learning models, data pipelines, and operational processes. You will collaborate with software development, machine learning, and robotics teams to ensure seamless maintenance of our data pipeline and deployment of AI systems.
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