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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.

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

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.

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.

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.

Lead the financial strategy at Bedrock by overseeing long-range planning, capital allocation, and building the FP&A function while providing strategic support to various business units.

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 Site Operations Manager will lead the deployment of autonomous construction technology, ensuring site launches, operational performance, and strong partner relationships throughout project lifecycles.