Live roles / lm-studio
Compatibility brief · Discovered by NoBoards 5h ago

Software Engineer, Inference Runtime

lm-studio · New York City
Sponsorship not statedRemote listedIndustry: software
Extracted role summary · not eligibility evidence

Inference runtime software engineer at LM Studio to advance on-device/cloud inference stack: integrate engines, bring up model architectures, optimize CPU/GPU runtimes, and contribute upstream (Python/C++, PyTorch, llama.cpp/MLX/vLLM).

PythonC++PyTorchllama.cppMLXExecuTorchvLLMSGLangTensorRT-LLMCUDA

LM Studio is used by millions of people around the world to run AI on their own computers, and now with Bionic - also in the cloud. Our values prioritize putting the human in the center, and creating tools that we want to use ourselves, and recommend to our friends and family.

As a team, we work with high technical intensity and personal responsibility. We are looking for curious, self-motivated, creative, and technically excellent teammates to join us and build the future of human-AI interactions in software.

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