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Machine Learning Manager Jobs in Colorado (NOW HIRING)

AppFolio

Principal Machine Learning Engineer

Denver, CO

We're transforming Property Management; how property managers operate, how residents live, and how ... Who We Are Looking For We're seeking a Principal Machine Learning Engineer to help define and lead ...

Apply Early

AppFolio

CO

We're transforming Property Management; how property managers operate, how residents live, and how ... Who We Are Looking For We're seeking a Principal Machine Learning Engineer to help define and lead ...

AppFolio

Staff Machine Learning Engineer

Denver, CO

We're transforming Property Management; how property managers operate, how residents live, and how ... Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML ...

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Machine Learning Manager information

See Colorado salary details

$53.6K

$85.9K

$124.1K

How much do machine learning manager jobs pay per year?

As of Jul 4, 2026, the average yearly pay for machine learning manager in Colorado is $85,918.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,400.00 and $97,300.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and their role involves understanding algorithms, data processing, and model deployment. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and overseeing complex AI solutions, making complete replacement unlikely in the near term.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning manager or director, often involving leadership, advanced technical skills, and strategic responsibilities. These roles usually require extensive experience, expertise in AI tools and frameworks, and may include performance-based bonuses or stock options that contribute to the total compensation. Such salaries are common in large tech companies or organizations with significant AI investments.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

Is ML a high paying job?

Machine Learning Managers typically earn high salaries due to the specialized skills required, such as expertise in algorithms, programming, and data analysis. Compensation varies based on experience, location, and industry, but it is generally above average compared to many other tech roles.

Which 3 jobs will survive AI?

Machine Learning Managers will continue to be essential as they oversee AI projects, interpret complex data, and coordinate teams, tasks that require strategic thinking and human judgment. Roles that involve creative problem-solving, emotional intelligence, and domain-specific expertise, such as healthcare professionals, educators, and skilled tradespeople, are also likely to persist despite AI advancements. These jobs rely on human intuition and adaptability that AI cannot fully replicate.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Colorado? The most popular types of Machine Learning jobs in Colorado are:
What are popular job titles related to Machine Learning Manager jobs in Colorado? For Machine Learning Manager jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Machine Learning Manager jobs in Colorado look for? The top searched job categories for Machine Learning Manager jobs in Colorado are:
What cities in Colorado are hiring for Machine Learning Manager jobs? Cities in Colorado with the most Machine Learning Manager job openings:
Machine Learning Manager jobs near you
Infographic showing various Machine Learning Manager job openings in Colorado as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 6% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $85,918 per year, or $41.3 per hour.
Principal Machine Learning Engineer

Principal Machine Learning Engineer

AppFolio

Denver, CO

Full-time

Posted 4 days ago

Be an early applicant

AppFolio rating

7.0

Company rating: 7.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

154th of 202 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 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. 
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.

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