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

Lead and scale all accounting operations (GL, revenue recognition, AP/AR, payroll, consolidations, equity), drive month-end close, oversee fintech revenue streams, build internal controls and systems, partner with FP&A and product/engineering to automate financial workflows, support audits, SOX readiness, and board/investor reporting.

Design and implement onboard control algorithms and system models for heavy construction robots, develop MPC and RL-based controllers, perform system identification and simulation of multi-DOF arms and vehicle dynamics, and ensure safety-critical real-time embedded performance.

Drive hardware reliability for autonomous construction machines: define reliability strategy and requirements, lead DFMEAs and FTAs, build reliability models and tests (HALT/HASS, ALT), run FRACAS and root-cause investigations, qualify suppliers, and convert field failures into design and process improvements.

Develop and deploy perception algorithms and analytics for re-identification and productivity/safety metrics on large construction sites. Integrate raw sensor data (camera, lidar, IMU), adapt perception signals for customer-facing analytics, work with customers to scope capabilities, and deploy models to fleets of machines while designing evaluations and analyzing sensor data.

As a Machine Learning Engineer, you will design and train perception models for robotics, focusing on 3D perception systems. You will tackle complex physical challenges, optimize models for embedded hardware, and collaborate with cross-functional teams.

Develop and scale learning models for behavior cloning and reinforcement learning. Build data pipelines and evaluate model performance for integration into autonomous systems.

Architect and maintain the embedded Linux stack for autonomous systems, optimize performance, and lead cross-functional technical efforts.

The Robotics Application Engineer leads deployment of autonomous excavators, conducts site evaluations, troubleshoots issues, collaborates on technical strategy, and communicates value to customers.

Lead end-to-end product quality across hardware development, manufacturing, supplier quality, reliability testing, and deployed robotic fleets. Establish IQC/IPQC/OQC, quality gates, FMEA and CAPA processes, define validation and test strategies (HALT/HASS, HIL/SIL), drive root-cause analysis, KPIs (yield, DPPM, MTBF/MTTR), and build automated diagnostics and AI-enabled workflows to improve reliability and field uptime.

Build and scale high-fidelity simulation environments for autonomous construction machines. Develop simulation systems to support ML-based autonomy, improve realism and performance (including terrain deformation), guide scene generation and neural rendering work, and produce production-quality simulation code and content to validate autonomy and safety at scale.