Jobs at Bedrock Robotics

The Frontend Engineer will establish UI interactions, architecture, and workflows, working with complex data and operating in a fast-paced startup environment. Responsibilities include designing frontend systems, optimizing performance, and collaborating with engineers across disciplines.

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.

The Technical Program Manager will manage execution across departments, anticipate risks, shape roadmaps, and drive critical initiatives to expand the deployment of autonomous construction machinery.

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.

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

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.

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.