Top Data Engineer Jobs in San Francisco, CA
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The Machine Learning Engineer will work on NLP projects for Grammarly's Enterprise team, focusing on building AI products and capabilities that enhance communication in organizations. The role involves applying ML technologies, collaborating with cross-functional teams, and innovating to solve technical challenges at scale.
The Machine Learning Engineer will develop new ML solutions to enhance the safety and fairness of Grammarly products, working in cross-functional teams and using state-of-the-art ML techniques. Responsibilities include building scalable ML solutions, mentoring team members, and integrating risk mitigation technology while communicating technical results effectively.
As a Principal Machine Learning Engineer, you will develop and implement cutting-edge machine learning algorithms and train sophisticated models, collaborating with cross-functional teams to integrate AI functionalities into Atlassian products. Your role includes designing system architectures, conducting experiments, and guiding emerging ML engineers to ensure AI's transformative potential is realized across offerings.
The Senior Machine Learning Engineer will design and build services for ML modelers, integrate data streams to create efficient models, and lead MLOps initiatives. The role involves collaborating with various teams to enhance ML tools and infrastructure while maintaining production software and developing new solutions.
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The Lead Data Engineer will establish a vision for data architecture and build scalable data models and pipelines. Responsibilities include optimizing foundational datasets, ensuring data quality, improving data infrastructure, building analytical dashboards, and mentoring junior engineers.
The role entails using data and technology to enhance marketing operations by generating insights. Responsibilities include data analysis using SQL and Python, building revenue optimization models, aligning marketing planning with corporate strategy, and defining KPIs for performance measurement.
Apply advanced machine learning techniques to tasks such as natural language processing, speech analytics, time series, and recommendation systems. Partner with various teams to deploy solutions into production and drive firm-wide initiatives. PhD in a quantitative discipline with 5 years of experience or MS with 8 years of experience required. Strong analytical thinking and communication skills essential.
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, enhance ML engineering platforms, implement ML Ops, and write production-ready code. You will collaborate with teams to deliver projects, participate in scrum meetings, and contribute to evaluating new technologies.
The role involves building large-scale machine learning systems focused on connecting users within Roblox, developing features like People You May Know and Friendship Score, and mentoring junior engineers. You will influence product direction and define long-term ML strategies.
Seeking talented data engineers to build foundational datasets and pipelines for robust financial reporting. Partner with Finance, Monetization Engineering, Business Intelligence, and Data Science teams to support critical financial reporting and analysis needs. Design, build, and monitor scalable pipelines.
As a Principal Data Scientist at Capital One, you will lead the development of machine learning models to improve customer experiences and business outcomes. You will research and apply emerging technologies in AI, engage with business and product teams, and ensure robust operational integration of models to serve millions of customers.
Top Companies in San Francisco, CA Hiring Data + Analytics Roles
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