Top Machine Learning Engineer Jobs in San Francisco, CA

The Senior Machine Learning Engineer will develop and enhance a machine learning platform, supporting data scientists and engineers in building and deploying models. Responsibilities include defining best practices for ML service development, CI/CD management, and collaboration across teams.

Design and implement ML models and systems, collaborate with cross-functional teams, and advance R&D efforts in a fast-paced environment.

Develop machine learning-powered ads ranking models, create performance evaluation metrics, and collaborate with Data Scientists to enhance ad experimentation.

Lead a team in developing and optimizing a personalized video recommendation engine, focusing on machine learning infrastructure and A/B testing. Ensure system architecture scalability, performance, and reliability.

As a Staff Machine Learning Engineer, you will design and develop machine learning systems to prevent fraud, ensuring data quality and integrating diverse data sources while collaborating with cross-functional teams.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

Develop and improve machine learning models for Pinterest's various product surfaces, utilizing deep learning and advanced data processing.

Develop and execute ML technology stack vision for Ads, improve ML models, and enhance content understanding using LLMs in a collaborative environment.

The Engineering Manager - Machine Learning will lead a team developing ML models for growth personalization and financial insights, driving measurable impact across Plaid's products.

Lead the design, development, and scaling of machine learning systems to optimize Adobe's go-to-market strategies and improve customer experiences.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.

The Senior Machine Learning Modeler will lead the design and implementation of AI-driven models for forecasting and financial planning, collaborating across teams to create scalable ML architectures and tools for model interpretability.

The Machine Learning Modeler will design and scale intelligent systems, build forecasting models, and collaborate with analytics teams to make data-driven decisions at Block.

Develop and deploy ML models to combat financial crimes. Collaborate with cross-functional teams, maintain documentation, and lead ML best practices.

Lead the development of advanced machine learning models and AI solutions for customer support, focusing on chatbot and voice automation technologies.

The Senior Machine Learning Engineer will develop scalable ML systems, collaborate across teams to improve solutions, and manage critical ML infrastructure projects.

The Senior AI Scientist will lead ML/AI innovation for multimodal video models, develop production-grade ML models, and engage in research and representation at conferences.

The role involves building and improving systems for training AI models, focusing on algorithms and infrastructure for reinforcement learning. Responsibilities include enhancing performance, reliability, and usability of systems to support research.

Conduct applied research in robotics and develop ML pipelines for training models on data collected by Scale, collaborating with customers and cross-functional teams.

The Staff Machine Learning Engineer will lead the architecture for the Stripe Assistant, improve ML methods, mentor engineers, and ensure reliable, high-trust AI interactions with users.

Lead the design and deployment of machine learning models to detect fraud, collaborating with teams to optimize performance and effectiveness while integrating solutions into existing systems.

Develop machine learning models to prevent risky or abusive activities in financial transactions, ensuring a secure user experience for families using Cash App.

Develop advanced ML models for an advertising platform, focusing on performance and scalability. Lead technical strategy and collaboration across teams to enhance campaign automation and optimization.

Design and implement machine learning pipelines for fraud and payment systems, collaborating with data scientists and engineers to enhance reliability and decision-making.

As a Staff Machine Learning Engineer, you will lead the design, implementation, and optimization of machine learning models, collaborate cross-functionally, and drive AI strategy to enhance SailPoint's identity security solutions.