Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

The role involves developing and optimizing web applications for 3D graphics in a dental tech environment, requiring collaboration on frontend and backend integrations and ensuring high performance and quality standards.

Lead and inspire a new R&D engineering team focused on innovative CAD/CAM solutions, driving project execution and fostering a culture of continuous learning.

Support Dandy's priority projects by analyzing business problems, conducting analysis, synthesizing findings, managing projects, and improving operations.

The Corporate Sourcer will identify and engage talent for Finance, Legal, and People functions, maintaining candidate pipelines and fostering a data-centric approach to sourcing.

Lead the operational support and training strategy for a global dental practice technology company. Oversee training operations, optimize processes, and ensure effective onboarding across markets.

Dandy seeks a Staff Software Engineer to design scalable infrastructure, improve product quality, and collaborate across teams to enhance system performance in a high-growth environment.

Manage and grow a full-stack engineering team building reporting, onboarding, billing, and operational systems for enterprise dental customers. Drive delivery, technical decisions, cross-functional partnership, hiring, mentorship, and engineering practices to ensure reliable, maintainable production systems.

Design, build, and optimize backend and full-stack features for Dandy's manufacturing and supply-chain platform. Develop order routing, integrate CAD->CAM automation, provide real-time order status, and implement rules to smooth demand and optimize workloads while collaborating with product and stakeholders.

As a Learning Experience Design Lead, you'll create engaging learning content, manage educational programs, and collaborate with sales teams to enhance their skills.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.