The Role We are looking for an Inference Runtime Software Engineer to push forward LM Studio's inference stack on-device and in the cloud. You will integrate new inference engines and runtime capabilities, bring up new open-weight models and modalities, and optimize model execution for a wide range of CPU and GPU targets. You will also contribute improvements to the open-source projects we build on. Qualifications - Significant experience building production ML systems, inference runtimes, or performance-sensitive infrastructure - Strong programming ability in Python and C++ - Deep understanding of transformer architectures and the mechanics of model inference - Experience profiling CPU or GPU workloads and reasoning about compute, memory, synchronization, and data movement - Experience with PyTorch and inference systems such as llama.cpp, MLX, ExecuTorch, vLLM, SGLang, or TensorRT-LLM - Strong debugging instincts across model code, runtime internals, operating systems, and CPU or GPU execution - Takes personal responsibility for the correctness and performance of their work Bonus Qualifications - Past contributions to open-source inference runtime projects such as llama.cpp, MLX, ExecuTorch, vLLM, SGLang, or TensorRT-LLM Responsibilities - Maintain and push forward our inference stack on-device and in the cloud - Bring up new model architectures and multimodal models - Improve latency, throughput, memory use, and reliability across CPU, CUDA, Metal, Vulkan, and ROCm runtimes - Build runtime capabilities for model loading, batching, scheduling, caching, and distributed execution - Benchmark and diagnose correctness and performance problems across the inference stack - Contribute upstream to open-source projects such as llama.cpp and MLX Benefits - Competitive salary and equity grants - Great medical, vision, dental healthcare plans - Catered team lunch / expensed dinners in the office - Flexible PTO - Flexible WFH - Sun-drenched office in SoHo in NYC