About the role
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars. SR. THERMAL ENGINEER (FLUIDS ANALYSIS), AI SATELLITES (STARMIND) SpaceX is leveraging its experience deploying and operating the world’s largest satellite constellation to develop Starmind, a new constellation of satellites capturing solar energy in space to power low-cost, high-performance AI compute for Earth. Scaling AI in space is a thermal problem as much as a power and processing problem. With a dense compute payload dissipating hundreds of kilowatts, the thermal system must efficiently transfer heat to large radiators that reject it to space, under solar load, eclipse, and multi-mode AI duty cycles. You will join the StarmindThermal team, which owns the satellite cooling stack end-to-end. Rejecting hundreds of kilowatts of accelerator waste heat to space is limited by high-flux loads transferring heat to massive deployable radiators. No capable cooling architecture has been flown at this scale. As a Senior Thermal Engineer focused on fluids analysis, you own conjugate heat transfer and thermal-fluid analysis of cold plates, heat exchangers, and radiator channels and manifolds, and the system 0-D/1-D thermal-fluid network that sets flow split, ΔP budget, loop ΔT, and pump operating point. You co-evolve geometry and flow path with mechanical and fluid-systems owners under tight feedback from manufacturing and test. You sit where the local physics is hardest and the design decisions stick: predictions that close margins, ground in test, and drive rate-production hardware.
RESPONSIBILITIES: Own conjugate heat-transfer (CHT) and thermal-fluid analysis of high-performance cold plates, heat exchangers, and radiator channels for STARMIND satellites Own the system 0-D/1-D thermal-fluid network that sizes and balances the cooling loop: flow split, ΔP budget, loop ΔT, pump operating point Drive cooling-loop architecture trades with hardware and vehicle-level thermal teammates Co-evolve geometry, materials and processes with hardware owners to find mass producible, efficient thermal solutions Predict component and system performance under wide range of flow and thermal conditions Own pre-test prediction, test design, and model-test correlation for fluid component and integrated thermal tests Automate analysis workflows for re-running trades as designs and boundary conditions change BASIC