Top Machine Learning Engineer Jobs in San Francisco, CA

The Machine Learning Engineer will build and deploy data products, collaborate cross-functionally, improve customer experiences, and mentor others in AI methods.

Lead KYC modeling strategy, develop machine learning systems for customer onboarding and compliance, and oversee KYC monitoring and rules engine. Manage a team and align strategies with key stakeholders.

The Staff Machine Learning Engineer will design and launch AI-driven tools, collaborate with diverse teams, and innovate in AI solutions to enhance customer value and drive product strategy at Block.

The role involves developing machine learning models to minimize fraud losses, conducting analysis, and collaborating across business units to improve data-driven modeling solutions.

The Senior Machine Learning Engineer will build AI-driven customer support products, collaborate cross-functionally, and maintain large-scale ML systems, leveraging modern techniques for real-world impact.

The Machine Learning Lead will manage technology strategy for AI training data, develop models, optimize pipelines, ensure dataset quality, collaborate cross-functionally, and mentor engineers.

Lead and mentor a team of applied ML engineers at Cash App, focusing on building explainable ML systems to support decision-making across business teams.

Manage and lead a team of Analysts, focusing on marketing measurement, optimizations, and utilizing machine learning to enhance campaign performance for clients.

The role involves developing predictive models, applying machine learning for marketing insights, and executing experiments to evaluate campaign impacts.

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

Lead the Applied Machine Learning team for Cash App, managing ML engineers, developing AI tools, and fostering collaboration on data-driven insights.

Design and implement ML-powered features, optimize algorithms, and collaborate cross-functionally to elevate the ML platform and enhance user experiences.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

Develop and deploy machine learning models for risk assessment, collaborating with teams to enhance Gusto's product offerings while ensuring model performance and reliability.

As a Machine Learning Systems Engineer, you will build and scale AI infrastructure, leading projects and mentoring junior engineers, while focusing on the ML project lifecycle and system architecture.

The Staff Machine Learning Engineer will architect and optimize data infrastructure for multimodal AI models in oncology, focusing on data management and processing pipelines.

As a Senior Machine Learning Engineer, you will develop machine learning models, manage their lifecycle, build infrastructure, and collaborate with teams to enhance our capabilities in various ML areas.

The Software Engineer will collaborate with researchers to develop and deploy ML models for pricing, handling model operations and challenges.

The ML Engineer will manage the infrastructure for training ML models, optimize performance, and ensure scalability for large datasets in collaboration with research teams.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

Lead the design, development, and implementation of machine learning applications. Collaborate cross-functionally to deliver ML models that solve business problems and ensure best practices in ML engineering.

Develop machine learning models to detect and reduce fraud within Block's ecosystems, while collaborating with various teams to implement solutions.

The role involves developing an AI agent platform, building ML models, and enhancing user experiences with advanced algorithms. Collaboration and fast-paced execution are key.