Top Remote Machine Learning Jobs in San Francisco Bay Area, CA

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

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

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.

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.

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

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.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

As a Machine Learning Intern, you will work on advanced AI solutions, collaborate with teams to design ML systems, and analyze data to enhance user experiences at Dropbox.

Lead and mentor a team of machine learning engineers to develop AI-driven product features, ensure production quality, and align with strategic goals.

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.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

The Machine Learning Engineer will develop and deploy AI/ML solutions, collaborate with data scientists and engineers, and enhance the platform experience.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

Drive and implement machine learning applications, optimize practices, formulate hypotheses, and communicate requirements to enhance advertising strategies and systems.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Lead R&D to design and deploy ML models for conversational agents, enhance automation in customer support, and build scalable AI systems across business units.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

As an Edge Compute Associate, you'll work under mentorship to develop edge computing solutions for satellites, collaborating on machine learning implementations.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.