Teams at Shield AI

Develop state estimation and navigation algorithms for autonomous systems operating in GPS-denied environments. Build production-grade C++ software for embedded Linux robotic platforms, create modeling and simulation tools, and implement comprehensive testing and validation. Collaborate on roadmap planning and agile execution while improving benchmarking and performance-analysis pipelines. The role requires professional C++ expertise, state estimation algorithm experience, sensor-fusion familiarity, and the ability to deploy reliable autonomy software.

Develop deep learning and 3D computer vision models for state estimation, visual navigation, localization, depth, correspondence, and pose estimation. Own data preparation, training, evaluation, benchmarking, and reproducible workflows. Integrate learned measurements into VIO and terrain-relative navigation systems, optimize models for onboard compute, and collaborate with deployment, software, systems, and flight-test teams to deliver production-ready Hivemind SDK components.

Leads Shield AI’s Enterprise Data delivery organization, managing data engineering, analytics engineering, domain enablement, and governance teams. Translates enterprise data strategy into sequenced roadmaps, manages priorities, capacity, dependencies, risks, and stakeholder expectations, and ensures production-ready, governed data products. Partners with architecture, platform engineering, security, and business leaders on technical tradeoffs, data quality, lineage, reliability, and investment priorities. Also owns hiring, coaching, performance development, delivery metrics, and continuous improvement of the data operating model.