Teams at The ePlane Company

Develops high-performance, differentiable multiphysics simulation and optimization software for electric aircraft design. Responsibilities include implementing numerical solvers, coupling machine-learning and physics models, validating simulations, building surrogate and reduced-order models, exposing analytic gradients, and optimizing GPU execution for throughput and latency. The role requires expertise in computational engineering, numerical methods, automatic differentiation, CUDA or equivalent compute frameworks, multidisciplinary design optimization, aerospace sizing, and surrogate modeling.

Architect and develop GPU-accelerated optimization and machine learning systems for aircraft design and urban air mobility operations. The role involves building coupled multi-physics and ML models, reinforcement learning and planning tools, C++ and Python APIs, spatial-query systems, and high-throughput simulation software. The engineer will own platform architecture, model validation, verification, performance optimization, and guidance on model reliability across engineering, operations, and commercial applications.

Develop and maintain internal platform services, engineering tools, deployment pipelines, and backend systems supporting machine learning, optimization, simulation, and mobility engineering teams. Responsibilities include algorithm development, system design, testing, code reviews, troubleshooting performance bottlenecks, and deploying reliable, high-performance tools and services.