Software Engineer, Inference Runtime

Lm-Studio; New York (NY); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive salary and equity grants

Excellent medical, vision, dental care

Catered team lunch / expensed dinners

Flexible PTO

Flexible WFH

Sun-drenched office in SoHo in NYC

Job summary

LM Studio in New York is seeking an Inference Runtime Software Engineer to advance our on-device and cloud inference stack. You will integrate new inference engines, optimize execution across CPU and GPU, and contribute to open-source projects.

You will also bring up new models and modalities, improve latency and memory use, and ensure reliability across diverse runtimes and hardware. Join a highly skilled team shaping human‑AI interactions.

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.

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

Skills

Python

C++

Transformer models

Inference runtimes

Profiling

PyTorch

Tools

llama.cpp

MLX

ExecuTorch

vLLM

SGLang

TensorRT-LLM

Job description

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