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Machine Learning Manager Jobs in Colorado (NOW HIRING)

AppFolio

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 ...

AppFolio

Sr. Machine Learning Engineer

Denver, CO

$107K - $147K/yr

We're transforming Property Management; how property managers operate, how residents live, and how ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

AppFolio

CO

$107K - $147K/yr

We're transforming Property Management; how property managers operate, how residents live, and how ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

Cleerly

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126K - $166K/yr

Our commitment to continually improving our products and processes proactively manages risks ... About the Opportunity We are seeking a senior machine learning software engineer to design, build ...

Cleerly, LLC

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126K - $166K/yr

Our commitment to continually improving our products and processes proactively manages risks ... About the Opportunity We are seeking a senior machine learning software engineer to design, build ...

Cleerly

Sr. Machine Learning Software Engineer

Denver, CO · On-site

$126K - $166K/yr

Our commitment to continually improving our products and processes proactively manages risks ... About the Opportunity We are seeking a senior machine learning software engineer to design, build ...

Code, LLC

Director of AI & ML

Denver, CO · On-site

Team Management: Lead, mentor, and inspire a cross-functional team of data scientists, machine learning engineers, and AI specialists. Foster a culture of innovation, collaboration, and continuous ...

Code, LLC

Director of AI & ML

Denver, CO

Team Management: Lead, mentor, and inspire a cross-functional team of data scientists, machine learning engineers, and AI specialists. Foster a culture of innovation, collaboration, and continuous ...

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All JobsMachine Learning Manager JobsMachine Learning Manager Jobs in Colorado

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 Jun 13, 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.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning executive or specialized researcher, often requiring advanced skills, extensive experience, and leadership responsibilities. These roles may involve overseeing AI strategy, managing teams, and working with cutting-edge tools and frameworks, and they are usually found in large tech companies or innovative organizations offering top-tier compensation.

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 machine learning manager?

A machine learning manager oversees teams developing and deploying machine learning models and algorithms. They coordinate projects, set strategic goals, and ensure technical quality, often requiring knowledge of data science, programming, and project management tools. Their role involves collaboration with data scientists, engineers, and stakeholders to implement AI solutions effectively.

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, data analysis, and programming languages like Python or TensorFlow. Salaries vary based on experience, location, and industry, but overall, it is considered a well-compensated role in the tech field.

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. Roles requiring high-level strategic thinking, creativity, and emotional intelligence—such as healthcare professionals, educators, and skilled tradespeople—are also likely to persist despite AI advancements. These jobs often involve tasks that are difficult for AI to replicate fully.

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

Staff Machine Learning Engineer

AppFolio

CO

Full-time

Posted 12 days ago

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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