{"schemaVersion":"jobsearcher.job.v1","id":"9fa9796882fde4ce561785b8","url":"https://jobsearcher.com/jobs/9fa9796882fde4ce561785b8","canonicalUrl":"https://jobsearcher.com/jobs/9fa9796882fde4ce561785b8","title":"Sr. Machine Learning Engineer","description":"Hi, We're AppFolio\nWe're innovators, changemakers, and collaborators. We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do business. We're transforming Property Management; how property managers operate, how residents live, and how intelligence flows across an entire industry.\nRealm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products, and a core layer delivering intelligent, high-impact experiences directly to our customers.\nAt its core, Realm-X is built on a structured domain ontology and a set of shared business primitives—such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making.\nWho We Are Looking For\nWe're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio's production voice and chat agent pipelines, working at the intersection of LLM agent frameworks, real-time voice technology, and streaming infrastructure.\nYou will work with Product, Voice channel, and ML Platform teams to translate cutting-edge agent and voice research into reliable, low-latency, multi-channel experiences that scale across our entire customer base.\nYour Impact\nShip Voice & Text Agents: Architect and ship voice and text agent pipelines that handle real-time, multi-turn customer interactions.\nReasoning vs. Latency: Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.\nLead a Pod: Lead a small pod of ML and platform engineers; raise the bar on agent evaluation, observability, and incident response.\nDefine Quality: Partner with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality.\nOptimize for Voice: Drive selective Small Language Model (SLM) fine-tuning and inference optimization for voice latency and cost.\nQualifications\nYou have shipped production AI agents serving real users in voice and/or text channels.\nYou think in pipelines and systems, not just models.\nYou move fast, deliver impact, and maintain sound engineering judgment.\nYou are humble, collaborative, and low-ego, and you elevate those around you.\nYou value work-life balance as a foundation for sustained high performance.\nMust Have\nAgent frameworks: Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).\nVoice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands the trade-offs between end-to-end voice models and modular STT → LLM → TTS architectures.\nLLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.\nTelephony & cloud: Production experience with Twilio (or comparable telephony) and AWS.\nEngineering: Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.\nML fundamentals: Solid foundation in deep learning, model evaluation, and inference optimization; able to deploy with Docker on AWS.\nLeadership: Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.\nNice to Have\nExperience fine-tuning Small Language Models for domain-specific voice applications.\nFamiliarity with RAG over structured business data and tool-using agents over API surfaces.\nPrior experience in regulated or customer-facing industries with strict reliability requirements.\nPublicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.\nLocation\nFind out more about our locations by visiting our site.\nAll late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.\nCompensation & Benefits\nThe compensation that we reasonably expect to pay for this role is: 167,200 - 209,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.\nPlease note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.\n\nRegular full-time employees are eligible for benefits - see here.\n\n#LI-KB1","company":"AppFolio","rawCompany":"appfolio","city":"Columbus","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-08-19T17:03:57.614Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sr. Machine Learning Engineer","description":"Hi, We're AppFolio\nWe're innovators, changemakers, and collaborators. We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do business. We're transforming Property Management; how property managers operate, how residents live, and how intelligence flows across an entire industry.\nRealm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products, and a core layer delivering intelligent, high-impact experiences directly to our customers.\nAt its core, Realm-X is built on a structured domain ontology and a set of shared business primitives—such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making.\nWho We Are Looking For\nWe're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio's production voice and chat agent pipelines, working at the intersection of LLM agent frameworks, real-time voice technology, and streaming infrastructure.\nYou will work with Product, Voice channel, and ML Platform teams to translate cutting-edge agent and voice research into reliable, low-latency, multi-channel experiences that scale across our entire customer base.\nYour Impact\nShip Voice & Text Agents: Architect and ship voice and text agent pipelines that handle real-time, multi-turn customer interactions.\nReasoning vs. Latency: Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.\nLead a Pod: Lead a small pod of ML and platform engineers; raise the bar on agent evaluation, observability, and incident response.\nDefine Quality: Partner with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality.\nOptimize for Voice: Drive selective Small Language Model (SLM) fine-tuning and inference optimization for voice latency and cost.\nQualifications\nYou have shipped production AI agents serving real users in voice and/or text channels.\nYou think in pipelines and systems, not just models.\nYou move fast, deliver impact, and maintain sound engineering judgment.\nYou are humble, collaborative, and low-ego, and you elevate those around you.\nYou value work-life balance as a foundation for sustained high performance.\nMust Have\nAgent frameworks: Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).\nVoice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands the trade-offs between end-to-end voice models and modular STT → LLM → TTS architectures.\nLLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.\nTelephony & cloud: Production experience with Twilio (or comparable telephony) and AWS.\nEngineering: Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.\nML fundamentals: Solid foundation in deep learning, model evaluation, and inference optimization; able to deploy with Docker on AWS.\nLeadership: Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.\nNice to Have\nExperience fine-tuning Small Language Models for domain-specific voice applications.\nFamiliarity with RAG over structured business data and tool-using agents over API surfaces.\nPrior experience in regulated or customer-facing industries with strict reliability requirements.\nPublicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.\nLocation\nFind out more about our locations by visiting our site.\nAll late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.\nCompensation & Benefits\nThe compensation that we reasonably expect to pay for this role is: 167,200 - 209,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.\nPlease note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.\n\nRegular full-time employees are eligible for benefits - see here.\n\n#LI-KB1","datePosted":"2026-08-19T17:03:57.614Z","dateModified":"2026-08-19T17:03:57.614Z","hiringOrganization":{"@type":"Organization","name":"AppFolio","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Columbus","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"9fa9796882fde4ce561785b8"},"url":"https://jobsearcher.com/jobs/9fa9796882fde4ce561785b8"}}