Top Remote Machine Learning Jobs in Los Angeles, CA
Seeking a Senior Staff Machine Learning Engineer with expertise in AI research to lead experimental projects optimizing large language models and enhancing model training strategies. Responsibilities include conducting experiments, publishing findings, and continuously refining AI models.
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.
Lead Machine Learning Engineer responsible for developing and implementing analytical capabilities, machine learning models, personalization services, and data products/services for a healthcare marketplace. Collaborates with data scientists, mentors junior engineers, and addresses technical challenges for product development.
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Seeking an experienced engineer to join the Machine Learning Foundations team to build self-service tooling for the model lifecycle, collaborate with internal customers, and work on the entire machine learning lifecycle.
Senior Machine Learning Engineer responsible for developing cutting-edge ML models and algorithms for company-wide metrics and GTM attribution. Partner with stakeholders to refine growth strategy and inform investment decisions with data.
Design, build, and manage distributed services and pipelines for underwriting and credit at Cash App. Lead projects, maintain high code quality, collaborate with teams, solve technical problems, and mentor engineers.
Lead a team of engineers to build one of Dropbox’s newest AI offerings, Dash. Foster operational excellence, streamline processes, and eliminate redundancies to ensure team agility. Provide strategic direction and contribute to technical and product strategies.
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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.
Experienced Machine Learning Engineer responsible for designing, implementing, and managing infrastructure for ML models in a collaborative environment. Must have deep understanding of ML concepts, proficiency in Python, Java, and Scala, and experience with cloud platforms like GCP, AWS, or Azure.
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