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