Staff ML Engineer: Scale AI Infra & Realm-X

Appfolio; Denver (CO); Hybrid; USD 200,000 - 275,000; Full time

Job summary

AppFolio is seeking a Staff Machine Learning Engineer to advance the ML platform that powers our AI initiatives—training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep the AI cloud always-on, observable, and economical while staying close enough to applications to influence model and agent design.

This role sits at the intersection of ML infrastructure, applied AI, and cost discipline. You will collaborate with Voice & Agents and Research ML engineers to turn prototypes into

Qualifications

• ML infra at scale: production ML infrastructure on AWS — ECS, SageMaker, GPUs, autoscaling, and cost controls.
• Inference platforms: model serving for LLMs and custom models; understands quantization, batching, and routing.
• Provider breadth: experience integrating with Google Vertex/Gemini, OpenAI, and Anthropic APIs in production.
• Training capability: trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference.
• Cloud-native engineering: strong Python, Docker, dependency management, and CI/CD for AI workloads.
• RAG & agents: working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data.
• Cost optimization: reducing unit cost of AI workloads without regressing quality or latency.
• AI safety & authorization: hands-on experience with AI guardrails, scoped tool permissions, and authorization layers for production AI systems.

Responsibilities

• Design and operate ML infrastructure on AWS — ECS, SageMaker, GPUs, model serving, autoscaling, and cost controls.
• Drive AI cost discipline across all AI applications: provider routing, caching, batch vs real-time, model-size selection, and inference economics.
• Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks.
• Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation.
• Productionize research by partnering with V&A and Research ML engineers to harden prototypes into production systems with SLOs and observability.
• Operate AI safety and guardrails: guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions.

Skills

ML infra at scale

Inference platforms

Provider breadth

Training capability

Cloud-native engineering

RAG & agents

Cost optimization

AI safety & authorization

Education

Bachelor’s/Master’s/PhD in CS or related

Tools

AWS

ECS

SageMaker

GPUs

LangChain

LangGraph

Job description

AppFolio is seeking a Staff Machine Learning Engineer to advance the ML platform that powers our AI initiatives—training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep the AI cloud always-on, observable, and economical while staying close enough to applications to influence model and agent design.

This role sits at the intersection of ML infrastructure, applied AI, and cost discipline. You will collaborate with Voice & Agents and Research ML engineers to turn prototypes into