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Artificial Intelligence Machine Learning Engineer Jobs in Roggen, CO

Signifyd

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 ...

STI

Artificial Intelligence ("AI") Architect

Denver, CO · On-site +1

... * Assist engineers in evaluating GenAI solutions and vendors to ensure they meet the state ... machine learning, deep learning, natural language processing, and computer vision. * 5+ years of ...

Tribonet

Product Development AI Engineer

Denver, CO · On-site

$100 - $125/hr

Position Summary Gates Corporation is seeking a Product Development AI Engineer to accelerate innovation across our global product portfolio by applying artificial intelligence, machine learning, and ...

Premier Inn Hotels LLC (UAE)

EE/CS Patent Agent

Denver, CO · On-site

$150 - $200/hr

... software engineering, computer science, or physics. Preferred experience includes patent prosecution in Artificial Intelligence , Machine Learning , 5G-Telecom , Robotics and Semiconductor ...

New

G2M Insights

Data Engineer

Denver, CO · On-site

$100 - $125/hr

We combine strategy, analytics, artificial intelligence, and software engineering to build trusted ... Supporting AI and machine learning initiatives * Collaborating with consultants to translate ...

Booz Allen Hamilton

Data Engineer, Mid

Aurora, CO · On-site

$77K - $176K/yr

... machine learning, and artificial intelligence. In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data engineer at Booz Allen, you ...

Booz Allen Hamilton, Inc.

Data Engineer, Mid

Aurora, CO · On-site

$77K - $176K/yr

... machine learning, and artificial intelligence. In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data engineer at Booz Allen, you ...

Booz Allen Hamilton, Inc.

Data Engineer, Mid

Aurora, CO · On-site +1

$77K - $176K/yr

... machine learning, and artificial intelligence. In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data engineer at Booz Allen, you ...

Deloitte

Senior AI Engineer - SFL Scientific

Denver, CO · On-site

$107K - $147K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Artificial Intelligence (AI). The team has a proven track record serving large, market-leading ...

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Showing results 21-40

All JobsArtificial Intelligence Machine Learning Engineer JobsArtificial Intelligence Machine Learning Engineer Jobs in Roggen, CO

Artificial Intelligence Machine Learning Engineer information

See Roggen, CO salary details

$34.9K

$142.8K

$214.6K

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

As of Sep 8, 2026, the average yearly pay for artificial intelligence machine learning engineer in Roggen, CO is $142,778.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,500.00 and $171,900.00 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 cities near Roggen, CO are hiring for Artificial Intelligence Machine Learning Engineer jobs?

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

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Roggen, CO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $142,778 per year, or $68.6 per hour.

Machine Learning Engineer / MLOps Engineer

Bet365

Denver, CO

Full-time

Re-posted 3 days ago

Bet365 rating

8.9

Company rating: 8.9 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

2nd of 15 rated gambling companies

Job description

hackajob is collaborating with Bet365 to connect them with exceptional professionals for this role.

We are seeking a highly pragmatic, results-driven Machine Learning (ML) Engineer to join our newly established US Data team. In this role, you will build the reliable, automated infrastructure that powers our machine learning lifecycle.

Your primary mission is to operationalize and scale the models developed by our data science team, taking them from prototype to robust, production-grade systems with high velocity.

You’ll focus on building reliable, automated and maintainable systems, keeping solutions pragmatic rather than over-engineered. You will also be passionate about automation, software engineering excellence, and MLOps.

You will report to the Data Science Team Leader and work in close alignment with the US AgentOps Team Lead (responsible for agentic and model orchestration platforms) and our UK technical excellence center. You will act as the bridge between model development and reliable platform engineering.

Preferred Skills and Experience

  • Proven experience as an ML Engineer, Data Engineer, or Software Engineer with a clear focus on deploying, monitoring, and scaling machine learning systems in production.

  • A pragmatic, proactive approach to system design, prioritizing speed, reliability, and business value over complex, theoretical infrastructure.

  • Strong Python programming skills, with a solid grasp of software engineering patterns, API development, and automated testing frameworks.

  • Extensive hands-on experience with Google Cloud Platform (GCP).

  • Practical experience with Vertex AI (specifically Vertex AI Pipelines, Endpoints, and Workbench).

  • Proficiency with containerization (Docker) and container orchestration tools.

  • Excellent communication skills, with the ability to translate software engineering concepts for data scientists and operational requirements for product leads.

  • Experience utilizing Infrastructure as Code (IaC) tools such as Terraform.

  • Experience running containerized workloads on Google Kubernetes Engine (GKE).

  • Familiarity with real-time streaming tools like Apache Kafka or GCP Pub/Sub.

What you will be doing

  • Owning the deployment of machine learning models to production. Build and maintain scalable, low-latency prediction endpoints using GCP Vertex AI.

  • Designing, implementing, and maintaining CI/CD/CT (Continuous Integration, Continuous Delivery, Continuous Training) pipelines for machine learning workflows using Vertex AI Pipelines, Cloud Build, and related GCP tools.

  • Setting up automated monitoring and alerting frameworks (e.g., Vertex AI Model Monitoring) to track data drift, model drift, and system performance in real-time.

  • Championing best practices for software engineering within the Data Science team, including robust unit testing, containerization, version control, and CI/CD automation.

  • Working closely with the Data Science Team Leader, Junior Data Scientists, and the AgentOps Team Lead to accelerate deployment cycles, remove operational bottlenecks, and maintain high deployment velocity.

What Bet365 employees say

Pay

Benefits

Hours and flexibility

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