Top Machine Learning Jobs in San Francisco, CA

The Principal Machine Learning Engineer will lead the development of recommendation systems for Disney's streaming platforms. Responsibilities include designing algorithms, collaborating with data science and product teams, and optimizing user experiences across various services. The role emphasizes building scalable ML pipelines and effectively communicating with both technical and non-technical stakeholders.

The role involves shaping the technical vision for credit and underwriting platforms at Cash App, mentoring engineers, and ensuring system reliability and maintainability. The position requires hands-on coding and leadership in large-scale projects, while collaborating with various stakeholders to enhance engineering systems and improve product features.

As a Senior Machine Learning Engineer, you will design scalable recommendation systems, preprocess data, train machine learning models, and enhance user engagement through personalized content recommendations. You will collaborate with cross-functional teams and implement feedback systems to improve model effectiveness.

The Applied AI Scientist at ZS develops algorithms for large data sets, executes statistical techniques, evaluates emerging datasets, and contributes to thought leadership by researching and publishing evolving topics.

The role involves designing and building services and tools for machine learning teams, integrating diverse data streams to build models, leading MLOps efforts, and influencing team culture at Block. The senior engineer will also prototype new tools and advocate for best practices.

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.

The Senior Machine Learning Engineer will build and deploy machine learning models to mitigate risks in payments, collaborate with cross-functional teams, develop scalable frameworks, and effectively communicate results to stakeholders.