Principal Machine Learning Engineer

Description

Hi, We’re AppFolio

We’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.

Realm-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.

At 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.

Who We Are Looking For

We’re seeking a Principal Machine Learning Engineer to help define and lead the next generation of AI systems within Realm-X.

This is a company-impact role. You will own mission-critical AI capabilities, shape long-term technical strategy, and act as a technical visionary and advisor across teams and leadership.

You’ll operate at the intersection of traditional machine learning, deep learning, and generative AI, building systems that go beyond AI assistance into execution, automation, and optimization.

This role is for someone who doesn’t just build systems — but redefines how they should be built.

Your Impact:

• Architect & Lead: Own the technical vision and architecture for AI systems across Realm-X in partnership with senior leadership.
• Scale Intelligent AI Agents: Design and deploy advanced AI Agentic systems that combine reasoning, planning, and execution.
• Improve the Foundation: Establish platform primitives and abstractions to enable context-aware, action-oriented AI that goes beyond simple assistance to true automation. Improve the standards for end-to-end ML systems: data collection, model training, evaluation, deployment, and inference infrastructure.
• Production Excellence: Architect and build scalable, multi-modal, and real-time AI applications, ensuring high-quality deployment standards.
• ML for Real Estate: set the technical foundation for training, fine-tuning, evaluating, and deploying open source LLM and SLM to production for optimizing performance, latency, and cost.
  
  
  

Qualifications

• You think in terms of systems, platforms, and long-term leverage, not just features.
• You’ve built and scaled ML/AI systems in production with meaningful business impact.
• You operate effectively in high ambiguity, turning unclear problems into a clear direction
• You’ve led or influenced large, cross-team technical initiatives.
• You introduce new ideas, architectures, or paradigms—not just implement existing ones.
• You bring a founder / owner-operator mindset: you take ownership, act with urgency, and focus on outcomes.
• You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment.
• You are humble, collaborative, and low-ego, and you elevate those around you.
• You value work-life balance as a foundation for sustained high performance.
  
  
  

Must Have:

• Master’s or Ph.D. in Computer Science, Machine Learning, or a related field (required).
• 10+ years of experience building software systems, with significant focus on ML/AI (or equivalent impact).
• Deep expertise across Traditional Machine Learning, Deep Learning, Generative AI / LLMs (prompting, fine-tuning, RAG, agents, tool, and skills use)
• Strong understanding of the full ML lifecycle: data extraction, model training, evaluation, and deployment. ML models integration in production software.
• You are an expert in Python, PyTorch, Numpy, AWS, Docker, SQL, embeddings, and RAG.
• You have experience with LangChain, LangGraph, and LLM observability tools (LangSmith).
• Experience designing and operating production-grade ML systems at scale
• Proficiency with AI coding tools and workflows (e.g., Copilot, ChatGPT, code generation tools)
  
  
  

Nice to Have:

• Experience with ontology-driven systems, knowledge graphs, or semantic layers
• Experience designing evaluation and benchmarking systems for AI
• Background in distributed systems and real-time architectures
• Experience building platforms used by multiple engineering teams
• Contributions to industry thought leadership (publications, talks, open source, etc.)
  
  
  

Compensation & Benefits

The compensation that we reasonably expect to pay for this role is: $264,000 - $330,000 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.

Please 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.