Jobs at Bedrock Robotics

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.

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

Lead cross-functional programs that deliver cloud infrastructure, data platforms, and user-facing applications for autonomous construction systems. Align engineering, commercial, and operations workstreams, mitigate technical and program risk, shape roadmaps and lightweight PM practices, and drive safety-critical validation for physical deployments.

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

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.

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

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.

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.