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Top Machine Learning Jobs in Santa Cruz, CA
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eCommerce • Fintech • Hardware • Payments • Software • Financial Services
The Staff Machine Learning Engineer will lead projects focusing on developing intelligent machine learning solutions for Square's products. Responsibilities include collaborating with leaders to define success criteria, driving machine learning projects, and mentoring team members, while advocating for engineering best practices and maintaining high code quality.
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
The Staff Machine Learning Engineer will shape the technical vision for credit and underwriting platforms, providing architectural direction while actively coding to solve complex challenges. Responsibilities include mentoring engineers, refining distributed systems, and collaborating with cross-functional teams to enhance feature delivery and engineering excellence.
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
The Staff Machine Learning Engineer will work with product and marketing teams to personalize user experiences, build and deploy machine learning models, and improve growth and engagement through data-driven insights. They will utilize machine learning algorithms and techniques to drive personalization across Cash App and Afterpay.
Featured Jobs
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.
Artificial Intelligence • Machine Learning • Natural Language Processing • Software
The Research Scientist will lead the development of Latent Space Models to advance voice AI capabilities. Responsibilities include creating neural audio codecs, generative models for human speech synthesis, embedding systems for data control, and optimizing architecture for scalable performance in real-time applications.
Cloud • Hardware • Healthtech • Information Technology • Mobile • Other • Infrastructure as a Service (IaaS)
The QA Data Engineer enhances quality and reliability of data-driven applications by developing automated validation tools, implementing data verification tests, and designing QA architecture for data processing. Responsibilities include performance testing on AI systems, creating data monitoring systems, and exploring new technologies to optimize data QA processes.
Top Skills:
Ai ToolsData Validation ToolsData WarehousingETLMachine LearningMS OfficeNoSQLPythonQa FrameworksScalaSQL
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
As a Senior Machine Learning Engineer at Samsara, you'll develop ML solutions for physical operations, driving new initiatives and optimizing systems. Collaborate with engineering teams to create end-to-end ML applications while influencing industry practices and contributing to company culture.
Computer Vision • Healthtech • Information Technology • Logistics • Machine Learning • Software • Manufacturing
As a Computer Vision/Machine Learning Engineer at Dandy, you will develop advanced computer vision models, collaborate with product teams, and work on 3D generative AI tasks. Your role involves researching state-of-the-art machine learning methods, managing large datasets, and implementing MLOps best practices to enhance dental technology solutions.
Top Skills:
PythonPyTorch
Artificial Intelligence • Marketing Tech • Software
As a Machine Learning Engineer, you will contribute to building and deploying machine learning models for a content recommender system, collaborate with data engineers, and derive insights to improve performance through modeling ideas and feature creation.
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