Staff Machine Learning Engineer

AppFolio is hiring a Staff Machine Learning Engineer (Denver, CO, hybrid) to advance the ML platform for Realm-X. Responsibilities Design and operate AppFolio’s ML infrastructure on AWS including ECS , SageMaker , GPU fleets , model serving, autoscaling, and cost controls Optimize cost across AI applications using provider routing, caching, and batch vs. real-time approaches, plus model size selection and inference economics Maintain reliable multi-provider LLM access across Google , OpenAI , and Anthropic with sensible fallbacks and abstractions Build training and fine-tuning pipelines for Small Language Models , including data pipelines, GPU orchestration, and evaluation Partner with Voice & Agents and Research ML engineers to harden prototypes into production systems with SLOs , on-call rotations , and observability Operate AppFolio’s AI safety and authorization layer including guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions Requirements 7+ years of experience developing and scaling web-based applications , preferably in a SaaS environment Systems thinker focused on platforms and long-term leverage Production builder with ML infrastructure experience delivering meaningful business impact Ability to operate in high ambiguity , converting unclear infrastructure problems into clear direction Owner-operator mindset with urgency and outcome focus Desire to move fast and deliver impact while maintaining sound engineering judgment Low-ego, collaborative approach that elevates others Values work-life balance as a foundation for sustained high performance Reliability mindset for ML infrastructure: SLOs , on-call , observability, and postmortems Built and operated production ML infrastructure at scale on AWS (ECS, SageMaker, GPUs, autoscaling, cost controls) Production inference platform experience for LLMs and custom models , including quantization, batching, and routing Production experience integrating Google (Vertex / Gemini) , OpenAI , and Anthropic APIs Trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference Strong Python and container/CI practices: Python , Docker , dependency management, and CI/CD for AI workloads Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data Demonstrated experience reducing unit cost without regressing quality or latency Hands-on experience with AI safety & authorization : guardrails, scoped tool permissions, and authorization layers Technologies AWS, ECS, SageMaker, GPU fleets Python, Docker, CI/CD Google (Vertex / Gemini), OpenAI, Anthropic LangChain, LangGraph, RAG Small Language Models Benefits Regular full-time employees are eligible for benefits (see here) Nice to Have Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline Experience training Small Language Models for production use GPU performance tuning (vLLM, TensorRT, Triton, or similar) Prior Staff-level role at a company with a significant AI infra footprint Experience with ontology-driven systems or knowledge graphs supporting AI applications Contributions to open-source ML infrastructure or LLM tooling Location Denver, CO (hybrid) Find out more about locations by visiting the company site All late-stage candidates complete an in-person meeting with an AppFolian as part of the hiring process Compensation & Benefits Base pay range: $200,000 - $275,000 Actual compensation determined by skills, education, experience, and internal equity Total Rewards includes additional benefits and potential discretionary bonuses depending on role and employment type #J-18808-Ljbffr AppFolio Inc