# Software Engineer, Application at Lm Studio > Onsite · United States · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Alm-studio%3Abd889236-2c5c-4c78-ad2f-2e7f84fe8717 (read 2026-11-11). ## Facts (observed) - Company: [Lm Studio](https://alderhq.app/companies/lm-studio) - Location text: New York City - Where it can be done from (inferred): Onsite · United States (evidence: "Location: New York City") - Posted: 2026-08-06 (97 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-08 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/lm-studio/bd889236-2c5c-4c78-ad2f-2e7f84fe8717 - Skills listed (inferred): TypeScript, React, Swift/iOS, Distributed systems ## Pay and sponsorship - Posted pay: $175k–$275k per year (from the listing's pay field) - Market band for similar posted roles (New York, n 812): p25 $145k, median $180k, p75 $225k ## Description (the employer's text) 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 Application Software Engineer to craft polished, intuitive, and performant experiences across our products. You will work closely with design to turn new AI capabilities into software that feels fast, thoughtful, and natural to use. You will own ambitious features from concept through launch, working across web technologies and native platforms as the problem requires. This role is for someone who cares deeply about product quality and pairs exceptional UI craft with the technical depth to profile performance, understand the operating system underneath, and solve problems across application and systems boundaries. Responsibilities Build polished, intuitive, and performant UI for the LM Studio desktop application and LM Link Collaborate with our design team to craft and ship top-tier experiences and workflows Dream up the interfaces of the future state of agentic interactions, always asking the question: how will agents help LM Studio users accomplish their goals? Obsess over the reliability and performance of what you build, profiling and testing across edge cases Diagnose problems across application, runtime, native platform, and operating system boundaries Qualifications 3+ years experience building application frontends, ideally for an Electron or native desktop product Deep expertise in TypeScript and React, or Swift and Objective-C Know how to profile application performance and trace problems through the software stack Understand the operating system beneath the application, including processes, threads, memory, filesystems, networking, and platform APIs Love the craft of high-end UI Think and build in terms of the overall user workflow while still sweating the small stuff Thrive in a fast-paced, shipping-oriented environment 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 Our Interview Process We are looking for engineering excellence and strong values / cultural fit. If your application appears to be a good match we'll reach out to schedule an initial call. If all goes well, we will proceed to 2-3 technical interviews. The final step in the process is an onsite interview in our New York office, where you will work through several more technical sessions focused around system design and architecture, meet the team and see how we work. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Alm-studio%3Abd889236-2c5c-4c78-ad2f-2e7f84fe8717 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.