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Principal Machine Learning Engineer

Job in Goleta, Santa Barbara County, California, 93116, USA
Listing for: AppFolio Inc
Full Time position
Listed on 2026-11-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 264000 - 363000 USD Yearly USD 264000.00 363000.00 YEAR
Job Description & How to Apply Below

App Folio 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 App Folio'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, Num Py, AWS, Docker, SQL
    , embeddings, and RAG
  • Experience with Lang Chain
    , Lang Graph
    , and LLM observability tools (Lang Smith)
  • 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, Num Py
  • AWS, Docker
  • SQL, embeddings, RAG
  • Lang Chain, Lang Graph, Lang Smith
  • 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 App Folio's site
  • All late-stage candidates complete an in-person meeting with an App Folian 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
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