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

As a Staff Mechanical Engineer, you'll integrate sensors and hardware into autonomous construction machines, ensuring durability and performance through collaboration with various teams and hands-on prototype support.

The role involves integrating simulators into the Cloud platform, ensuring reliable simulation workflows, and collaborating with simulation engineers to optimize efficiency.

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.

Own and evolve the developer platform: design and operate CI/CD, monorepo tooling, GitHub automation, and self-service developer workflows to improve build reliability, speed, and engineering productivity across the org.

Lead design and build core backend services and infrastructure for autonomous construction equipment, including fleet management, task orchestration, monitoring, tooling for testing and deployments, and collaboration with frontend, ML, and robotics teams.

Build and productionize AI-driven annotation systems and agentic workflows for robot sensor data: auto-labelers, orchestration, quality harnesses, versioning, metrics, and integrations to support perception and autonomy.

Design, build, and maintain scalable data ingestion and ETL pipelines across a growing data lake. Define and enforce data quality standards, SLOs, and validation frameworks. Optimize pipelines for performance and cost, expand monitoring and alerting, and enable stakeholders to self-serve on data infrastructure.

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.

Lead data science across autonomy, safety, and product by analyzing machine telemetry and operational data, defining metrics, designing experiments, and partnering with ML platform and engineering to deliver insights that improve system performance and safety.