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Machine Learning Engineer Jobs in Colorado (NOW HIRING)

Ibotta

Staff Machine Learning Engineer

Denver, CO · On-site +1

$206K - $230K/yr

As a Staff Machine Learning Engineer, you will act as a technical leader and delivery owner for complex, high-impact ML initiatives spanning foundation models, data systems, and large-scale ML ...

True Anomaly

Machine Learning Engineer

Denver, CO · On-site

$85K - $180K/yr

Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a similar discipline * Proficient in Python * Foundational understanding of machine learning concepts ...

Ibotta

$206K - $230K/yr

As a Staff Machine Learning Engineer, you will act as a technical leader and delivery owner for complex, high-impact ML initiatives spanning foundation models, data systems, and large-scale ML ...

Workday

Machine Learning Engineer III

Boulder, CO

$60.50 - $81.25/hr

About The Role As a Machine Learning Engineer in Agent Factory, you'll design and build the core ML systems behind Workday's next generation of AI agents. Working within a small, senior, cross ...

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$107K - $147K/yr

The Senior Machine Learning Engineer will design, build, and deploy core machine learning and AI capabilities, working with a cross-functional team to advance technology in artificial intelligence ...

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$107K - $147K/yr

They are seeking a Senior Machine Learning Engineer to design, build, and deploy core machine learning and AI capabilities, working with a cross-functional team to enhance technology in the field of ...

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Machine Learning Engineer information

See Colorado salary details

$33.1K

$135.4K

$203.5K

How much do machine learning engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for machine learning engineer in Colorado is $135,403.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $163,000.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Colorado? The most popular types of Machine Learning Engineer jobs in Colorado are:
What are popular job titles related to Machine Learning Engineer jobs in Colorado? For Machine Learning Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Colorado look for? The top searched job categories for Machine Learning Engineer jobs in Colorado are:
What cities in Colorado are hiring for Machine Learning Engineer jobs? Cities in Colorado with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in CO? For Machine Learning Engineer jobs in CO, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Machine Learning Engineer - Health AIML

Machine Learning Engineer - Health AIML

Apple

Boulder, CO • On-site

Full-time

Posted 20 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers, and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a senior engineer excited about solving real-world problems in the health domain that make a difference in our customers' lives.
In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning models and systems. You will solve ambitious problems involving unique data and high-impact products, including state-of-the-art generative AI technologies. The successful candidate should possess excellent interpersonal skills and the ability to work cross-functionally to rapidly apply engineering best practices and novel research techniques at the intersection of Health, ML, and consumer products.
10+ years of overall software development experience.Experience leading a team and/or a proven track record of cross-functional collaboration to deliver customer-facing features with machine learning capabilities in production.BS/MS/Ph.D. in Computer Science, Computer Engineering, Machine Learning, or related fields (or equivalent qualification).
Ph.D. in Computer Science, Machine Learning, or a related field.Strong background in generative models, natural language processing (NLP), and large language models (LLMs).5+ years of hands-on experience in state-of-the-art machine learning and deep learning applied to large-scale datasets and/or production applications.Proficiency developing and working with large-scale models using modern machine learning packages (e.g., TensorFlow, PyTorch, Jax, Huggingface).Proficiency in building and troubleshooting modern agentic systems (prompt tuning, routing, planning, multi-agent, RAG, tool use, memory management, etc.).Experience with healthcare data, products, and workflows.Ability to thrive in a fast-paced environment, deal with uncertainty, and adapt to new and changing requirements.Proven track record of contributing to diverse teams in a collaborative environment.A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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