Staff ML Platform Engineer

Appfolio; San Francisco (CA); On-site; USD 200,000 - 275,000; Full time

Job summary

AppFolio is seeking a Staff Machine Learning Engineer to advance the Realm-X ML platform, enabling training, fine-tuning, inference, and cost discipline across its AI initiatives. You will partner with the Voice & Agents and Research ML teams to productionize prototypes, ensure observability, and deploy scalable AI infrastructure.

You will design and operate AWS-based ML pipelines, manage multi-provider LLM access, and drive cost optimization while maintaining quality and reliability for our

Qualifications

• ML infra at scale: Has built and operated production ML infrastructure on AWS - ECS, SageMaker, GPUs, autoscaling, and cost controls.
• Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing.
• Provider breadth: Direct experience integrating with Google (Vertex / Gemini), OpenAI, and Anthropic APIs in production.
• Training capability: Has 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: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency.
• AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems.

Responsibilities

• Design and operate AppFolio's ML infrastructure on AWS - ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls.
• Drive AI Cost Discipline: Optimize cost across all AI applications - provider routing, caching, batch vs. real-time, model size selection, and inference economics.
• Multi-Provider Reliability: Maintain reliable, multi-provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions.
• Training & Fine-Tuning Stack: Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation.
• Productionize Research: Partner with Voice & Agents and Research ML engineers to harden their prototypes into production systems with SLOs, on-call rotations, and observability.
• AI Safety & Guardrails: Operate AppFolio's AI safety and authorization layer - guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions.

Skills

ML infra

Production ML

Python

Docker

CI/CD

LangChain

RAG patterns

Cost optimization

AI safety

Education

CS degree

Tools

AWS

SageMaker

GPUs

ECS

Job description

AppFolio is seeking a Staff Machine Learning Engineer to advance the Realm-X ML platform, enabling training, fine-tuning, inference, and cost discipline across its AI initiatives. You will partner with the Voice & Agents and Research ML teams to productionize prototypes, ensure observability, and deploy scalable AI infrastructure.

You will design and operate AWS-based ML pipelines, manage multi-provider LLM access, and drive cost optimization while maintaining quality and reliability for our