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Machine Learning Engineer Jobs in Broomfield, CO

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are ...

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 ...

Sr. Machine Learning Engineer

Denver, CO · On-site

$107K - $147K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Showing results 21-40

Machine Learning Engineer information

See Broomfield, CO salary details

$31.7K

$129.7K

$195K

How much do machine learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning engineer in Broomfield, CO is $129,743.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $156,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Broomfield, CO? The most popular types of Machine Learning Engineer jobs in Broomfield, CO are:
What are popular job titles related to Machine Learning Engineer jobs in Broomfield, CO? For Machine Learning Engineer jobs in Broomfield, CO, the most frequently searched job titles are:
What cities near Broomfield, CO are hiring for Machine Learning Engineer jobs? Cities near Broomfield, CO with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Broomfield, CO as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $129,752 per year, or $62.4 per hour.

Senior Machine Learning Engineer - AI Platform

Workday, Inc.

Boulder, CO • On-site

$127K - $167K/yr

Full-time

Re-posted 13 days ago


Workday rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

153rd of 242 rated software companies


Job description

Your work days are brighter here.
We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.
About the Team
Do you want to build AI-powered software that impacts millions of people every day? The AI Core team, part of Workday's AI Platform organization, tackles challenging problems at the intersection of machine learning, agentic reasoning, and enterprise-scale systems. Our work delivers critical AI platform capabilities and differentiated, deep-value agent applications.
About the Role
As a Machine Learning Engineer on the AI Core team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate with other engineers to deliver ML solutions across Workday's product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised. Additionally, you will develop and deploy new APIs/services using Docker/Kubernetes at scale and leverage Workday's vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge?
You are a strong technical leader with deep Python expertise and solid software engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently. Specifically, you will:
  • Own exploration, design and implementation of features for our sophisticated ML platforms, pipelines and services.
  • Be responsible for evaluation, scalability and observability of these features.
  • Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures
  • Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
  • Serve as a technical role model for more junior engineers

About You
Basic Qualifications:
  • Bachelor's (Master's or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent
  • 6+ yrs experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
  • 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models
  • 5+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)

Other Qualifications:
  • 3+ years of experience in building information retrieval systems and/or graph-based recommendation systems.
  • 3+ years of hands-on professional experience in developing large language models (LLMs), text generation models, or graph-based machine learning models for production, including data processing, model fine-tuning, model deployment and model evaluation
  • 3+ years of experience building services to host machine learning models in production at scale
  • 3+ years of experience in machine learning and deep learning frameworks & toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn
  • 3+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker
  • Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
  • Professional experience in independently solving ambiguous, open-ended problems and technically leading teams

Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.
Primary Location: USA.CO.Boulder
Primary Location Base Pay Range: $171,600 USD - $257,400 USD
Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD
Additional Considerations:
The application deadline for this role is the same as the posting end date stated as below:
08/09/2026
Our Approach to Flexible Work
With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.
Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.
In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

What Workday employees say

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About Workday

Sourced by ZipRecruiter

Workday's journey began with a transformative idea generated during a breakfast conversation between its founders in sunny California. What set us apart from the start was our people-centric culture, driven by the core value of prioritizing our employees. At Workday, the happiness, growth, and contributions of every team member are at the heart of who we are. Our collaborative and employee-focused culture is the key ingredient for our business success. We not only care for our people but also for the communities and the environment, all while maintaining profitability. Embrace your uniqueness, as we encourage our Workmates to shine brightly in their authentic selves. Our passion and energy make us distinct, and we are inspired to create a brighter workday for everyone.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

Pleasanton, CA, US

Year founded

2005