Principal Machine Learning Engineer

AppFolio is hiring a Principal Machine Learning Engineer to lead mission-critical AI capabilities for Realm-X and support autonomous real estate performance management (RPM).

Responsibilities

• Define the technical vision and architecture for AI systems across Realm-X in partnership with senior leadership
• Design and deploy advanced AI agentic systems combining reasoning, planning, and execution
• Build multi-agent orchestration across specialist agents such as maintenance, leasing, accounting, and collections
• Create platform primitives and abstractions for context-aware, action-oriented automation beyond assistance
• Raise end-to-end ML standards across data collection, model training, evaluation, deployment, and inference infrastructure
• Architect and build scalable multi-modal, real-time AI applications with strong deployment quality
• Drive AppFolio’s transition toward autonomous property management operations using existing LLMs while instrumenting proprietary data collection for targeted training, fine-tuning, and RL optimization of open-source LLMs and SLMs for RPM
• Optimize RPM outcomes across performance, latency, and cost
• Build data and feedback loops enabling Reinforcement Learning over agent action policies in a partially observable, high-stakes property management environment

Requirements

• Master’s or Ph.D. in Computer Science, Machine Learning, or a related field (required)
• 10+ years building software systems with significant focus on ML/AI (or equivalent impact)
• Published research and experience shipping production systems
• Strong foundation in traditional machine learning, deep learning, and generative AI / LLMs (prompting, fine-tuning, RAG, agents, tool and skills use)
• Direct hands-on experience with LLM post-training including SFT, RLHF, DPO, and/or RL at non-trivial scale
• Expertise in data extraction, model training, evaluation, deployment, and production software integration
• Expert in Python, PyTorch, NumPy, AWS, Docker, SQL, embeddings, and RAG
• Experience with LangChain, LangGraph, and LLM observability tools (LangSmith)
• Experience designing and operating production-grade ML systems at scale
• Applied experience with ontology-driven systems, knowledge graphs, or semantic layers for AI business-domain modeling
• Proficiency with AI coding tools and workflows (e.g., Copilot, ChatGPT, code generation tools)

Technologies

• Python, PyTorch, NumPy
• AWS, Docker
• SQL, embeddings, RAG
• LangChain, LangGraph, LangSmith
• Copilot, ChatGPT
• SFT, RLHF, DPO, LLMs, SLMs

Benefits

• Regular full-time employees are eligible for benefits
• Compensation range: $264,000 - $363,000 base pay
• Additional benefits or discretionary bonuses may be eligible based on role and/or employment type

Nice to Have

• Deep RL expertise for sequential decision-making under partial observability
• 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.)

Location

• Goleta, CA (onsite)
• Find out more about locations by visiting AppFolio’s site
• All late-stage candidates complete an in-person meeting with an AppFolian as part of the hiring process

Role Fit

• Systems thinker focused on platforms and long-term leverage
• Production builder with ML/AI scaling and meaningful business impact
• Works effectively in high ambiguity and turns unclear problems into direction
• Influence through leadership or cross-team technical initiatives
• Originality in introducing new architectures or paradigms
• Owner-operator mindset focused on outcomes and urgency
• Fast execution with strong engineering judgment
• Collaboration with humility and low ego
• Sustainability values work-life balance for sustained performance
• Vertical conviction interest in winning in real estate