Top Hybrid Machine Learning Jobs in San Francisco, CA
The Machine Learning Engineer will be part of Cash App's Risk ML team, working on identity verification and fraud detection using machine learning methods and systems. Responsibilities include reducing inauthentic identities, mitigating risk/fraud for the Cash Card product, and collaborating with cross-functional teams.
Design, build, and enhance batch inference services and tools using Generative AI and Machine Learning to detect and prevent illegal and suspicious activity on a financial platform. Lead infrastructure development, collaborate with cross-functional teams, and drive strategic roadmaps.
The Staff Machine Learning Engineer at Cash App's Financial Crimes Technology team will work on leveraging Generative AI and Machine Learning to detect and report illegal and suspicious activity on Cash App. Responsibilities include deploying AI copilot solutions, building classification models, and working with diverse data sets to improve agent productivity and eliminate manual decision loops.
Seeking a Principal Data Scientist with strong engineering skills to drive ML and AI capabilities across multiple teams. Responsibilities include hands-on development work, tech leadership, mentoring, and driving technical standards. Requires 8+ years of impactful experience in ML and AI implementation, deep hands-on experience with data products and infrastructure, and expertise in major technologies like Airflow, DBT, AWS, etc.
Hiring Senior Machine Learning Engineers to join the ML Platform team. Responsible for building a scalable Machine Learning platform.
Featured Jobs
Build, optimize, and deploy machine learning models for identity resolution and ads attribution. Collaborate with cross-functional teams and stay up-to-date with the latest technology. Strong understanding of machine learning approaches and algorithms.
Quality Engineering role working on Machine Learning technologies, involving test automation, AI/ML model testing, test plans creation, and troubleshooting.
As a Lead Applied Machine Learning Scientist at J.P. Morgan Chase, you will be responsible for developing machine learning models to detect and mitigate fraud risks in SMB payments. You will work on large datasets, collaborate with various teams, and drive the complete lifecycle of model development and deployment.
Design and build ML architectures and data pipelines for large-scale data repositories. Work on Clari's AI models and platform. Collaborate with stakeholders to deliver enterprise products. Fully remote opportunity in the United States.
Lead machine learning engineer responsible for developing deep learning vision algorithms for robotic grasping in practical automation applications. Collaborate with robotics and platform engineers to create AI-enabled robotic products.
As a Principal Machine Learning Engineer, you will work on the Perception and Prediction team to develop autonomous driving capabilities. You will drive R&D initiatives, design and train neural networks, prototype and deploy solutions, and mentor junior engineers. You will also have the opportunity to pioneer research and contribute to the culture of inclusion and innovation within the company.
Design and improve deep learning architectures for neural signals from novel hardware, scale up data collection and run experiments on large datasets, explore and invent novel ways to decode neural signals with low latency, collaborate with neuroscientists, ML engineers, and interaction designers.
Top hybrid Companies in San Francisco, CA Hiring Data + Analytics Roles
See All
.png)
All Filters
No Results
No Results
