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

The Staff Platform Engineer will manage Developer Infrastructure, focusing on build systems, testing infrastructures, and release pipelines to enhance developer velocity and system reliability, primarily using Bazel in a large monorepo environment.

The Research Platform Engineer will design and build critical infrastructure for AI research, optimize performance, and improve developer experience while collaborating with researchers.

The Research Engineer will enhance world models through multimodal data by building datasets, processing systems, and conducting experiments to improve model quality. Responsibilities include data acquisition, pipeline creation, and ensuring data's impact on model performance.

The Senior Platform Engineer will design and operate OLTP systems, manage production infrastructure, ensure reliability, and mentor team members.

Design, build, and operate scalable automated 3D data pipelines and high-performance rendering systems. Own synthetic data generation, data quality, observability, and distributed storage to support model training. Collaborate with product, research, and 3D artists; set technical direction and mentor engineers to productionize 3D data capabilities.

Lead full-stack development of user-centric web-based 3D graphics tools and backend generative AI services. Own features end-to-end, collaborate with research and design partners, ship responsive web apps, and iterate with early testers.

Build production-grade backend services and pipelines to turn 3D/ML research prototypes into reliable, debuggable features. Work across Python-based graphics/ML algorithms, FastAPI services, asset import/export integrations with DCC tools, and collaborate with frontend and research teams to ship reproducible, user-facing 3D workflows.

Design, implement, and optimize modern SLAM systems (visual, visual-inertial, lidar, multi-sensor). Build state estimation, sensor fusion, map management, loop closure, and benchmarking frameworks. Research hybrid learning-based SLAM, analyze failure modes, and productionize real-time, scalable mapping for downstream world-modeling applications.

Design, implement, and train large-scale diffusion models for generating 3D worlds. Drive end-to-end model development including data curation, experimentation, evaluation, deployment, and collaboration with research, engineering, and product teams. Mentor colleagues and integrate cutting-edge generative AI research into production-ready systems.

Own technical recruiting and sourcing systems to identify and engage top AI/ML/robotics researchers and engineers. Build scalable processes, maintain ATS pipelines, develop creative sourcing strategies (publications, conferences, open-source), partner with research leaders, manage candidate experience end-to-end, analyze hiring metrics, and support interview coordination and hiring operations.