Teams at ElastixAI

Design and optimize a low-level AI inference serving stack: customize open-source frameworks, build model partitioning/scheduling, integrate with proprietary accelerators, profile and optimize across Python orchestration to C++ kernels and drivers, and enable PyTorch-native deployment tooling.

Design and implement a novel AI inference engine through hardware-software co-design. Collaborate with ML, software, and cloud engineers; model PPA trade-offs; contribute to RTL design, simulation, verification, and roadmap planning to optimize inference for modern LLM workloads.

Conduct and lead applied ML research to develop efficient generative models and AI inference techniques. Prototype and implement novel methods, run experiments, write production-quality code, analyze results, and collaborate with engineering teams to transition research into scalable production systems.