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.

Develop and optimize sensor pipelines for autonomous construction machines, involving sensor calibration, validation, and data analysis in real-world conditions.

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.

Owner of corporate infrastructure projects: design and deploy identity, endpoints, networking, and SaaS integrations. Consult with business teams, write documentation/RFDs, modify IaC (HCL), script automations, define workplace tech standards for multi-site rollouts, and coordinate vendors from kickoff to handoff.

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.

Join a cutting-edge team deploying autonomous systems on construction machinery, enhancing safety and project efficiency in infrastructure projects.

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

The Hardware Engineer will design, integrate, and validate hardware for autonomous machines, working on system architecture and collaborating with engineers and vendors.

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