Top Machine Learning Jobs in San Francisco Bay Area, CA

The Machine Learning Intern will collaborate with engineering teams to oversee an ML project, gaining experience in the ML development lifecycle, and ultimately ship a production-ready feature.

As a Staff Machine Learning Engineer, you'll lead ML system strategy for fraud and risk management, use analytics for decision-making, and drive technical solutions across teams.

Design and implement ML models to combat financial crimes, collaborate with stakeholders, and maintain regulatory documentation while leading ML practices.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

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.

As a Senior ML Engineer, you'll design, develop, and deploy ML models for product features, collaborate with teams, and drive research initiatives.

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 AI/ML initiatives at Legion, develop forecasting models, manage a team of ML specialists, and engage with clients on tech adoption.

The Staff Machine Learning Engineer will develop ML systems for fraud prevention, lead signal discovery, and collaborate across teams on lending decision frameworks, mentoring peers, and owning solutions from design to deployment.

The Staff Machine Learning Engineer will build ML systems to enhance fraud prevention and risk decisions driving platform improvements and mentoring fellow scientists.

Lead and mentor a team of machine learning engineers to develop and deploy ML models supporting banking and lending services, while driving innovation and best practices.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

The Senior Staff Machine Learning Engineer will lead AI/ML initiatives, design scalable models, mentor engineers, and combat financial fraud through advanced methodologies.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

The Principal Machine Learning Engineer shapes the machine learning strategy and architecture, leads initiatives, mentors engineers, and influences technical decisions at SharkNinja.

As a Senior Machine Learning Engineer, you'll lead the design, development, and implementation of ML models to detect risks like fraud and account takeovers, while mentoring junior team members and collaborating with stakeholders to translate business needs into technical solutions.

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 model development to detect fraud, manage financial risks, and mentor other engineers. Responsibilities include system design, architecture, and applying AI/ML methodologies in a cross-team capacity.

The Senior Machine Learning Platform Engineer will develop ML models, mentor engineers, optimize systems, and enhance ML infrastructure at Coinbase.

As a Machine Learning Engineer in the Risk AI/ML team at Coinbase, you'll develop, enhance, and deploy ML models to prevent fraud and improve security for users. This role involves end-to-end model ownership, responding to threats, and collaborating with various teams to create automated defenses.

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 Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.