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Assistant Appfolio Jobs in Colorado (NOW HIRING)

AppFolio

Staff Machine Learning Engineer

Denver, CO

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 ...

AppFolio

CO · On-site

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 ...

AppFolio

CO

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 ...

AppFolio

CO · On-site

$107K - $147K/yr

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 ...

Atlas Real Estate

Assistant Turn Coordinator

Denver, CO · On-site

$21 - $26/hr

About the Role The Assistant Turn Coordinator is a field-based support role designed to help ... Use project tools and apps (AppFolio, Meld, or other field platforms) to log work completed

All JobsAppfolio JobsAssistant Appfolio JobsAssistant Appfolio Jobs in Colorado

Assistant Appfolio information

What is an Assistant Appfolio?

An Assistant Appfolio is typically a professional who supports property managers or real estate teams using the Appfolio property management software. Their primary responsibilities include helping with tenant communications, data entry, lease management, rent collection, and coordinating maintenance requests within the Appfolio platform. They ensure that property-related information is organized and accessible, helping streamline operations for property management companies. Assistant Appfolios play a vital role in keeping day-to-day tasks efficient and ensuring the software is used to its fullest potential.

What are the key skills and qualifications needed to thrive as an Assistant at AppFolio, and why are they important?

To thrive as an Assistant at AppFolio, you need strong organizational skills, attention to detail, and a background in administrative support or property management. Familiarity with property management software (especially AppFolio), office productivity tools, and CRM systems is typically required. Excellent communication, problem-solving, and multitasking abilities help you support teams and deliver superior customer service. These combined skills enable efficiency, accuracy, and effective collaboration in a fast-paced real estate technology environment.

What is the difference between Assistant Appfolio vs Assistant Yardi?

AspectAssistant AppfolioAssistant Yardi
CertificationsKnowledge of Appfolio platform, property management softwareKnowledge of Yardi platform, property management software
Work EnvironmentReal estate/property management firms using AppfolioReal estate/property management firms using Yardi
Industry UsageCommon in residential property managementCommon in residential and commercial property management
Job FocusAssisting with Appfolio software tasks, data entry, tenant communicationAssisting with Yardi software tasks, data entry, tenant communication

Assistant Appfolio and Assistant Yardi are similar roles supporting property management software platforms. The main difference lies in the specific software they support: Appfolio or Yardi. Both roles involve data entry, tenant communication, and administrative tasks within property management firms that use these platforms. The choice depends on the company's software system, but both roles require familiarity with property management processes and software-specific skills.

What are some common challenges faced by Assistant Appfolio users in property management roles, and how can they be addressed?

Assistant Appfolio users in property management often encounter challenges such as staying organized amid high volumes of tenant requests and ensuring accurate data entry for leases and payments. Navigating the software’s robust feature set can also be overwhelming initially. To address these challenges, it’s beneficial to participate in Appfolio’s training webinars, utilize the built-in knowledge base, and collaborate closely with team members to share best practices. Regularly updating workflows and leveraging automation tools within Appfolio can also help streamline tasks and reduce errors.
What are the most commonly searched types of Appfolio jobs in Colorado? The most popular types of Appfolio jobs in Colorado are:
Assistant Appfolio jobs near you
Staff Machine Learning Engineer

Staff Machine Learning Engineer

AppFolio

Denver, CO

Full-time

Posted 18 days ago

AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

155th of 209 rated software companies

Job 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 hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on — training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep our AI cloud always-on, observable, and economical, while staying close enough to applications to influence model and agent design.
This role works at the intersection of ML infrastructure, applied AI, and cost discipline. You'll partner closely with our Voice & Agents and Research ML engineers to harden their prototypes into production systems, and help move forward the platform layer that lets Realm-X scale across AppFolio's entire customer base.
Your Impact
  • ML Platform: 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.
Qualifications
  • Systems thinker: You think in terms of platforms and long-term leverage, not just features.
  • Production builder: You've built and scaled ML infrastructure in production with meaningful business impact.
  • Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction.
  • Owner-operator: You take ownership with a founder/owner-operator mindset, act with urgency, and focus on outcomes.
  • Pace: You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment.
  • Collaboration: You are humble, collaborative, and low-ego, and you elevate those around you.
  • Sustainability: You value work-life balance as a foundation for sustained high performance.
  • Reliability mindset: You treat ML infra like any other production system — SLOs, on-call, observability, postmortems.
Must Have
  • 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.
Nice to Have
  • Experience training Small Language Models for production use.
  • GPU performance tuning (vLLM, TensorRT, Triton, or similar).
  • Prior Staff-level role at a company with a significant AI infra footprint.
  • Experience with ontology-driven systems or knowledge graphs supporting AI applications.
  • Contributions to open-source ML infrastructure or LLM tooling.
Location
Find out more about our locations by visiting our site. 
Compensation & Benefits
The compensation that we reasonably expect to pay for this role is: $200,000 - 250,000 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.
Regular full-time employees are eligible for benefits - see here.
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