Principal Machine Learning Engineer
About The Position
AppFolio is seeking a Principal Machine Learning Engineer to define and lead the next generation of AI systems within Realm-X and drive the long-term autonomous Real Estate Performance Management (RPM) platform. This company-impact role owns mission-critical AI capabilities, shapes long-term technical strategy, and serves as a technical visionary and advisor across teams and leadership. The position works across traditional machine learning, deep learning, and generative AI to build systems that enable execution, automation, and optimization. The role helps establish technical vision and architecture for Realm-X AI systems, and designs and deploys advanced agentic systems that combine reasoning, planning, execution, and multi-agent orchestration. It also improves platform primitives and end-to-end ML standards spanning data collection, model training, evaluation, deployment, and inference infrastructure. The engineer will architect scalable, multimodal, real-time AI applications and support high-quality production deployment. A key focus is advancing autonomous property management operations. The engineer will use existing LLMs and instrument proprietary data collection to support selective training, fine-tuning, and reinforcement-learning optimization of open-source LLMs and SLMs for the RPM domain, with attention to performance, latency, and cost. The role also builds data and feedback loops for reinforcement learning over agent action policies in partially observable, high-stakes property management environments.
Requirements
- Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
- 10+ years of experience building software systems, with significant focus on ML/AI, or equivalent impact.
- Combined academic and industry track record, including published research and shipped production systems.
- Deep expertise in traditional machine learning, deep learning, and generative AI/LLMs, including prompting, fine-tuning, RAG, agents, and tool and skills use.
- Direct, hands-on experience with LLM post-training at non-trivial scale, including SFT, RLHF, DPO, and/or RL.
- Strong understanding of the full ML lifecycle, including data extraction, model training, evaluation, deployment, and integration into production software.
- Expertise in Python, PyTorch, NumPy, AWS, Docker, SQL, embeddings, and RAG.
- Experience with LangChain, LangGraph, and LLM observability tools such as LangSmith.
- Experience designing and operating production-grade ML systems at scale.
- Applied experience with ontology-driven systems, knowledge graphs, or semantic layers used to model business domains for AI systems.
- Proficiency with AI coding tools and workflows such as Copilot, ChatGPT, and code-generation tools.
- Systems-oriented perspective focused on platforms and long-term leverage.
- Ability to operate effectively amid ambiguity and turn unclear problems into direction.
- Demonstrated ability to lead or influence cross-team technical initiatives and introduce original ideas, architectures, or paradigms.
- Owner-operator mindset, urgency, outcome focus, and sound engineering judgment while moving quickly.
- Humble, collaborative, low-ego approach that elevates colleagues.
- Values work-life balance as a foundation for sustained performance and has genuine interest in the real estate industry.
Nice To Haves
- Deep reinforcement learning expertise applied to 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 through publications, talks, or open source.
Responsibilities
- Help define the technical vision and architecture for AI systems across Realm-X in partnership with senior leadership.
- Design and deploy advanced agentic AI systems combining reasoning, planning, execution, and multi-agent orchestration across specialist agents such as maintenance, leasing, accounting, and collections.
- Establish platform primitives and abstractions for context-aware, action-oriented AI and improve end-to-end ML standards for data collection, training, evaluation, deployment, and inference infrastructure.
- Architect and build scalable, multimodal, real-time AI applications and ensure high-quality production deployment.
- Drive AppFolio's transition toward autonomous property management operations, using current LLMs and instrumenting proprietary data collection for selective training, fine-tuning, and RL optimization of open-source LLMs and SLMs for the RPM domain.
- Optimize AI systems for performance, latency, and cost.
- Build data and feedback loops that enable reinforcement learning over agent action policies in partially observable property management environments.
- Own mission-critical AI capabilities, shape long-term technical strategy, and advise teams and leadership.
- Lead or influence large cross-team technical initiatives and turn ambiguous problems into clear direction.
Benefits
- Regular full-time employees are eligible for benefits; the posting directs candidates to a benefits page for details.
- The total rewards package may include discretionary bonuses depending on role and employment type.
- The company describes opportunities for growth and compelling total rewards, coaching and mentorship, and time and tools to develop skills.
- Hybrid work environment designed to be flexible, personal, and connected.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
