Top Data Engineer Jobs in San Francisco Bay Area, CA
As a Staff Machine Learning Engineer on the Bidding Policy team, you will build and implement ML models for accurate bidding decisions in high-volume auctions. The role entails end-to-end ownership of systems design, monitoring ML research, and collaboration with a team of engineers.
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As an ML Engineer at Notion, you will enhance the product by integrating AI technologies. Responsibilities include prototyping improvements in AI model quality, launching technology integrations into the product, collaborating with cross-functional teams, and staying informed on AI trends.
As a Senior Machine Learning Engineer at Samsara, you will develop ML solutions to enhance the safety, efficiency, and sustainability of physical operations. You will collaborate with engineering teams and cross-functional partners to deliver core infrastructure and optimize services across the ML pipeline.
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The role involves managing the accounting function, ensuring accurate financial records, preparing financial reports, analyzing data, and complying with regulations. Responsibilities include account reconciliations, journal entries, revenue recognition, and budget preparation. Candidates should have a strong accounting background and excellent analytical skills for continuous improvement in accounting processes.
The Staff Data Engineer will advance the Enterprise Data Platform by designing and developing data models, warehouses, and visualization solutions. Key responsibilities include optimizing ETL processes, collaborating with cross-functional teams to meet data requirements, and implementing data security and governance protocols while coaching junior staff.
The Machine Learning Engineer will create models to drive value for users and advertisers, evaluate technical tradeoffs, perform code reviews, and build scalable products while ensuring exceptional code quality.
As a Principal Data Scientist, you will conduct research and develop machine learning models, partner with engineering teams to deploy scalable systems, and collaborate with business units to improve customer experiences through data analysis.
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The Director of Data Operations will support the CDO in enhancing operational excellence within the Data Organization, manage high-impact projects, and facilitate cross-functional communication. Responsibilities include implementing data strategies, overseeing daily operations, managing budgets and vendor relationships, and leading team development initiatives.
The Privacy Analyst will work within Grammarly's Legal team to manage vendor privacy reviews, perform data protection assessments, and collaborate across various teams on privacy compliance projects. The role includes drafting resources for teams, participating in audits, maintaining privacy records, leading training, and developing privacy programs.
The Machine Learning Engineer will design, evaluate, and deploy large scale ML systems, collaborating with cross-functional teams to enhance user experiences. The role involves working with large data systems and evaluating ML system performance, along with participating in on-call rotations as needed.
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