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Machine Learning Engineer Jobs in Castle Rock, CO

Blissway Inc

Machine Learning Engineer

Denver, CO · On-site

$145K - $195K/yr

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 ...

AppFolio

Staff Machine Learning Engineer

Denver, CO · On-site

$200 - $250/hr

Overview Build and operate the ML platform that powers AppFolio's AI-native Real Estate platform, ensuring scalable training, inference, and cost‑efficient operations across AWS and ...

Cymertek

AI/ML Engineer

Aurora, CO · On-site

SIMILAR CAREER TITLES Machine Learning Engineer, Artificial Intelligence Engineer, Data Scientist, Deep Learning Engineer, NLP Engineer, Computer Vision Engineer, AI Research Scientist, Robotics ...

Paradigm

Senior ML Ops Engineer

Denver, CO · On-site

$123K - $170K/yr

... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ... Engineers, and Infrastructure teams to operationalize ML solutions and improve deployment ...

Cymertek

Data Scientist / Software Engineer

Aurora, CO · On-site

SIMILAR CAREER TITLES Data Engineer, Machine Learning Engineer, Software Engineer, Data Analyst, Research Scientist, Artificial Intelligence Engineer, Data Architect, Data Science Developer, Business ...

Cymertek

Software Engineer

Aurora, CO · On-site

... Machine Learning Engineer, AI Engineer, Robotics Software Engineer, etc. DEGREE (Level Desired) Bachelor's Degree DEGREE (Focus) Computer Science, Software Engineering, Information Technology ...

Bet365

Data Science Team Lead/Manager

Denver, CO

This is not a pure people-management role. • Building, mentoring, and guiding a pragmatic, delivery-focused team of Junior Data Scientists and Machine Learning Engineers, fostering a culture of ...

Bet365

Senior Data Scientist

Denver, CO

Collaborating with Machine Learning Engineers to champion the adoption of robust MLOps practices on our Google Cloud Platform (GCP) stack, ensuring models are automated, monitored, and scalable.

Deloitte

Senior AI Engineer - SFL Scientific

Denver, CO · On-site

$107K - $147K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Castle Rock, CO

Machine Learning Engineer information

See Castle Rock, CO salary details

$32.8K

$134.3K

$201.8K

How much do machine learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning engineer in Castle Rock, CO is $134,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,800.00 and $161,600.00 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.

More about Machine Learning Engineer jobs

What cities near Castle Rock, CO are hiring for Machine Learning Engineer jobs?

Cities near Castle Rock, CO with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Castle Rock, CO as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $134,282 per year, or $64.6 per hour.

Machine Learning Engineer

Blissway Inc

Denver, CO • On-site

$145K - $195K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 14 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. We've stayed under the radar, but our impact is visible on the massive Interstate Highway System connecting every major US metro (except Juneau, AK-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 isn'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 don't care what you're most proficient in today-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 camera'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're 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'll 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: you'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're 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're 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've worked and what you've built.
  6. Final In-Person: A chance to meet the team and see the work environment firsthand.

We'll 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 don'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 don'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 hobby-then come back and tell us all about it.

Fuel & Community
  • The Blissway Kitchen: Whether it'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 it-if we're missing your favorite fuel, just add it to the request list.
  • The "BlissTrip": An annual 3-4 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.

Apply