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Artificial Intelligence Machine Learning Engineer Jobs in Boulder, CO

Machine Learning Engineer

Denver, CO ยท On-site

$120 - $180/hr

Machine Learning Engineer The Mission: You are the engineer who ships the model, not just the one who trains it. At Blissway, we process 11 million images every single day, running detection ...

Senior ML Ops Engineer

Denver, CO ยท On-site

$123K - $170K/yr

... Artificial Intelligence or related field or equivalent experience. ยท 4+ years of professional experience in software engineering, machine learning engineering, MLOps, platform engineering, DevOps, ...

Artificial Intelligence Engineer

Denver, CO ยท On-site

$140K - $175K/yr

About the Opportunity: We are seeking an experienced Artificial Intelligence Engineer who ... Proficiency in Python and familiarity with deep learning/NLP libraries * Experience with building ...

... intelligence flows across an entire industry. Realm-X is AppFolio's AI-native platform powering ... Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML ...

Sr. Machine Learning Engineer

Denver, CO

$107K - $147K/yr

... intelligence flows across an entire industry. Realm-X is AppFolio's AI-native platform powering ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

Showing results 21-40

Artificial Intelligence Machine Learning Engineer information

See Boulder, CO salary details

$33.2K

$135.5K

$203.7K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for artificial intelligence machine learning engineer in Boulder, CO is $135,538.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,800.00 and $163,100.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

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

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

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

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Boulder, CO?

For Artificial Intelligence Machine Learning Engineer jobs in Boulder, CO, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Boulder, CO look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Boulder, CO are:

What cities near Boulder, CO are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Boulder, CO with the most Artificial Intelligence Machine Learning Engineer job openings:

Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Boulder, CO as of August 2026, with employment types broken down into 100% Full Time. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $135,538 per year, or $65.2 per hour.

Machine Learning Engineer

Blissway Inc.

Denver, CO โ€ข On-site

$120 - $180/hr

Other

Medical, Life, Retirement, PTO

Re-posted 17 days ago


Job description

Work at Blissway: Opportunity for Impact Every Day

Blissway is a startup that simplifies toll collection and dramatically improves highway safety. We are multiple startups in one: Deep Tech, AI/ML, Hardware, SaaS, and IoT. For the past five years, we have built a nearly insurmountable technological lead in tolling, an industry that is quietly bigger than football. While our competitors have thousands of employees, we operate with a lean but growing team of less than 30. Weโ€™ve stayed under the radar, but our impact is visible on the massive Interstate Highway System connecting every major US metro (except Juneau, AKโ€”sorry, Juneau).

You are a good fit if...
  • You love the grind: You take ownership and put in the time to meet deadlines. Our recent team survey showed an average of 55 hours/week, with occasional 70+ hour bursts for major releases.

  • You are detail obsessed: You have experience writing code that stands up to the unpredictability of the physical world, where the small details are the difference between success and failure.

  • You are adaptable: We are a lean team. If you only want to work on a "niche thing" or are uncomfortable helping other teams when they need a boost, this isnโ€™t the place for you. We expect you to figure out what you need to get stuff done.

  • You code really well: We mostly use Python and TypeScript, but we donโ€™t care what youโ€™re most proficient in todayโ€”as long as you learn fast.

Machine Learning Engineer

The Mission: You are the engineer who ships the model, not just the one who trains it. At Blissway, we process 11 million images every single day, running detection, segmentation, classification, embeddings, and re-identification across everything in the cameraโ€™s frame. You will own the full arc: raw sensor data to production inference, dataset curation to deployment monitoring, cloud to edge. This role is for the engineer who sees a model sitting in a notebook and feels the itch to put it to the test, or in this case, on the road.

The Work

  • Own the Whole Pipeline: You decide which problems are worth solving, then take them from raw sensor data all the way to production: collection, dataset curation, training, deployment, monitoring, and iteration. We wire it all together and run our own servers, so the pipeline is yours end to end.

  • Real Hardware in the Real World: This is the part that makes us special. We own the devices in the field. This means any idea you have can actually get built and tested on real roads.

  • Vision at Real Scale: We process 11 million images every single day, running detection, segmentation, classification, embeddings, and re-identification across everything in the frame: vehicles, license plates, wheels, even lane markings. Beyond images, we have multiple other sensors on the road pulling in different data making the problem space wide open. At this volume, the right model can drastically improve accuracy and cut cost at the same time.

  • Classical CV to Custom SOTA: Our toolbox spans the full range, from traditional computer vision algorithms to custom-trained state-of-the-art models (detection, segmentation, embeddings, classifiers). You pick the right tool, and when nothing off-the-shelf is good enough, you train your own.

  • Build the Best Models That Exist: We read the papers, go to the conferences, and hold our work to the current frontier. ML has become essential to Blissway over the past year, and this team is where that bet gets made real.

  • Edge and Cloud: Most of our compute lives in the cloud where power is effectively unlimited. We are now pushing more inference onto the roadside hardware itself, a completely different problem: the models have to be fast, small, and power-efficient without giving up accuracy. You will work both sides of that constraint.

Requirements

  • Experience: 2 to 6 years of software engineering with a focus on machine learning and/or computer vision. We want someone with true end-to-end experience: youโ€™ve taken models from raw data to production and owned what happens after they ship.

  • Both Sides: Strong software engineering fundamentals plus hands-on ML. You write production-quality code and you train and debug models. The two overlap, and we want someone comfortable across both.

  • Full Lifecycle: You\'ve owned models beyond the notebook: trained, deployed, monitored, and iterated in production.

  • Real CV depth. Experience with modern computer vision and the judgment to know when a classical technique beats a heavy model. You\'re not reaching for a transformer when a filter will do.

How We Work

We are a small team, which means a more deliberate interview process than you might be used to. In exchange, you get real autonomy from day one, direct access to the people setting technical direction, and work that ships to real roads in weeks, not quarters.

The Process: We hire software engineers in cohorts. Rather than evaluate candidates on a rolling basis, we collect applications over a two-week window and assess everyone together. This allows us to make fair, considered comparisons and move the strongest candidates through the process efficiently and fairly.

The process has five stages:

  1. Application Review: We (a human) read every application carefully at the close of the approximately two-week window.

  2. Ezra: A brief AI-assisted screening to make sure we are a mutual fit before investing more of your time. Think of this as a way to augment your application.

  3. Screening Interview: A focused conversation to understand your background and motivations.

  4. Technical Interview: A deeper evaluation of your skills and how you think through problems.

  5. Experience Interview: A conversation about how you have worked and what you have built.

  6. Final In-Person: A chance to meet the team and see the work environment firsthand.

We will be in touch at the close of the application window with next steps.

The Essentials (Health & Wealth)

  • Relocation Support: We are excited for you to join the team at our engineering office in Denver. We value in-person collaboration and daily team lunches and we provide a relocation bonus to help you get here.

  • Personalized Health Coverage (ICHRA): We donโ€™t believe in one-size-fits-all healthcare. We provide a monthly allowance for you and dependents so you can choose the individual plan that actually fits your life.

  • Investing in Your Future: 401(k) matching up to 4%.

  • Peace of Mind: Transparent compensation. Company-sponsored life & disability insurance.

  • Early Stage Equity: Competitive equity package with 24-month exercise window. Every year, we facilitate a tender process that gives you the opportunity to sell your vested shares at the same valuation as our investors.

Rest & Recharge

  • High-Trust Time Off: 4 weeks of untracked PTO. We donโ€™t micromanage your calendar; we focus on your impact. Take the time you need to stay sharp and inspired.

  • Family First: 12 weeks of paid parental leave for birth and adoptive parents. We want you present for the moments that matter most.

  • The Deep Breath (Sabbatical): Every 5 years, take 12 weeks of fully paid leave. Go travel, write a book, or master a new hobbyโ€”then come back and tell us all about it.

Fuel & Community

  • The Blissway Kitchen: Whether itโ€™s breakfast to start your day or our daily group lunches, we keep the team fueled.

  • Snacks Autonomy: Our kitchen is fully stocked and we mean itโ€”if weโ€™re missing your favorite fuel, just add it to the request list.

  • The "BlissTrip": An annual 3โ€“4 day getaway for the team and significant others.

  • Monthly Beats: Game nights, escape rooms, and dinners to celebrate the grit we put in.

  • Continuous Learning: Tuition reimbursement for courses, programs, and conferences that sharpen your craft.

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