2

Remote Machine Learning Architect Jobs in California

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

Showing results 41-60

Remote Machine Learning Architect information

What is a remote machine learning architect?

A Remote Machine Learning Architect is a professional who designs, builds, and oversees machine learning systems and infrastructure while working remotely. They collaborate with data scientists, engineers, and stakeholders to define system architecture, select appropriate algorithms, and ensure scalable deployment of machine learning models. Their responsibilities include setting technical standards, optimizing workflows, and ensuring integration with existing IT infrastructure, all accomplished through remote communication and collaboration tools. This role requires strong expertise in machine learning, cloud platforms, and software engineering.

How does a remote machine learning architect typically collaborate with distributed teams to deliver successful projects?

As a Remote Machine Learning Architect, effective collaboration with globally distributed teams is essential. You will often coordinate with data scientists, software engineers, and business stakeholders via virtual meetings, shared documentation, and project management tools. Regular communication, clear documentation of model designs, and version control practices are crucial to ensure alignment and smooth integration of machine learning solutions. Adopting agile methodologies and being proactive in addressing time zone differences help maintain project momentum and foster a productive team environment.

What are the key skills and qualifications needed to thrive as a remote machine learning architect, and why are they important?

To thrive as a Remote Machine Learning Architect, you need deep expertise in machine learning algorithms, model development, and a solid background in computer science or related fields, often supported by an advanced degree. Familiarity with cloud platforms (such as AWS, Azure, or GCP), deep learning frameworks (like TensorFlow or PyTorch), and relevant certifications are typically expected. Strong problem-solving, communication, and project management skills help you collaborate effectively with distributed teams and stakeholders. These skills and qualities are crucial for designing scalable ML solutions that drive business value in a remote work environment.

What is the difference between Remote Machine Learning Architect vs Data Scientist?

AspectRemote Machine Learning ArchitectData Scientist
Required CredentialsMaster's or PhD in CS, AI, or related fields; certifications in ML frameworksMaster's in Data Science, Statistics, or related; certifications in data analysis tools
Work EnvironmentDesigning ML systems, collaborating with engineering teams, remote or on-siteAnalyzing data, building models, often remote or in-office
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Remote Machine Learning Architects focus on designing and implementing scalable ML systems, while Data Scientists analyze data and build models. Both roles require advanced degrees and often overlap in skills, but their core responsibilities differ in scope and focus.

What are popular job titles related to Remote Machine Learning Architect jobs in California?

For Remote Machine Learning Architect jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Architect jobs in California look for?

The top searched job categories for Remote Machine Learning Architect jobs in California are:

What cities in California are hiring for Remote Machine Learning Architect jobs?

Cities in California with the most Remote Machine Learning Architect job openings:

Infographic showing various Remote Machine Learning Architect job openings in California as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% Remote job distribution.

Principal Machine Learning Engineer

AppFolio, Inc.

Santa Barbara, CA • On-site, Remote

Full-time

Re-posted 22 days ago


AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

184th of 245 rated software companies


Job description

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, and to drive AppFolio's long-term autonomous Real Estate Performance Management (RPM) platform - autonomous AI agents that can deliver property management performance.
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: Help define 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, including multi-agent orchestration across specialist agents (e.g., maintenance, leasing, accounting, collections).
  • 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 Autonomous Property Management: Drive AppFolio's transition toward autonomous property management operations. Use existing LLMs today and instrument the proprietary data collection now that will let us selectively train, fine-tune, and RL-optimize open source LLM and SLM for the RPM domain - optimizing performance, latency, and cost.
  • Reinforcement Learning for Agent Policies: Build the data and feedback loops needed to enable Reinforcement Learning over agent action policies in the partially observable, high-stakes property management environment.

Qualifications
  • Systems thinker: You think in terms of systems, platforms, and long-term leverage, not just features.
  • Production builder: You've built and scaled ML/AI systems in production with meaningful business impact.
  • Ambiguity: You operate effectively in high ambiguity, turning unclear problems into a clear direction.
  • Influence: You've led or influenced large, cross-team technical initiatives.
  • Originality: You introduce new ideas, architectures, or paradigms - not just implement existing ones.
  • Owner-operator: You bring a founder / owner-operator mindset: you take ownership, 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.
  • Vertical conviction: You bring genuine interest in winning a specific industry vertical (real estate) rather than chasing horizontal AI hype.

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).
  • Combined academic and industry track record: Published research and shipped production systems.
  • Deep ML expertise: Traditional Machine Learning, Deep Learning, and Generative AI / LLMs (prompting, fine-tuning, RAG, agents, tool and skills use).
  • LLM post-training: Direct, hands-on experience with LLM post-training - SFT, RLHF, DPO, and/or RL - at non-trivial scale.
  • Full ML lifecycle: Strong understanding of data extraction, model training, evaluation, deployment, and integration into production software.
  • Core stack: Expert in Python, PyTorch, NumPy, AWS, Docker, SQL, embeddings, and RAG.
  • Agent tooling: Experience with LangChain, LangGraph, and LLM observability tools (LangSmith).
  • Production ML at scale: Experience designing and operating production-grade ML systems at scale.
  • Ontology & knowledge graphs: Applied experience with ontology-driven systems, knowledge graphs, or semantic layers used to model business domains for AI systems.
  • AI-native engineering: Proficiency with AI coding tools and workflows (e.g., Copilot, ChatGPT, code generation tools).

Nice to Have
  • Reinforcement Learning depth: Deep RL 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 (publications, talks, open source, etc.).

Location
Find out more about our locations by visiting our site.
All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.
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.
Regular full-time employees are eligible for benefits - see here.
#LI-KB1
About AppFolio
AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com.
Why AppFolio
Grow We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves.
Learn We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills.
Impact We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities.
Connect We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed.
Paddle as One.
Learn more at appfolio.com/company/careers
Statement of Equal Opportunity
At AppFolio, we value diversity in backgrounds and perspectives and depend on it to drive our innovative culture. That's why we're a proud Equal Opportunity Employer, and we believe that our products, our teams, and our business are stronger because of it. This means that no matter what race, color, religion, sex, sexual orientation, gender identification, national origin, age, marital status, ancestry, physical or mental disability, or veteran status, you're always welcome at AppFolio.

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