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Ai Automation Testing Jobs in Colorado (NOW HIRING)

Amplifire

Sr. QA Automation Engineer

Boulder, CO · On-site

$120K - $135K/yr

You will also help apply AI-assisted testing approaches where they can reduce repetitive work ... What You'll Do Automation, Manual Testing & Quality Fundamentals * Build and maintain automated ...

Compunnel

Automation Developer

Greenwood Village, CO · On-site

... AI tools to assist with development, scripting, and troubleshooting while testing, reviewing, and validating generated output. Required Qualifications • 3-7 years of experience in software ...

Eliassen Group

Test Automation Engineer

Englewood, CO · On-site

$55 - $65/hr

The role covers automation and manual testing for customer-facing web and mobile portals and ... All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring ...

Eliassen Group

Test Automation Engineer

Englewood, CO · On-site

$55 - $65/hr

The role covers automation and manual testing for customer-facing web and mobile portals and ... All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring ...

Eliassen Group

Test Automation Engineer

Englewood, CO · On-site

$55 - $65/hr

The role covers automation and manual testing for customer-facing web and mobile portals and ... All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring ...

Themesoft Inc

Remote_QA tester-AI Agentic

Denver, CO · On-site

$100 - $125/hr

Hands-on experience with API testing (Postman, Swagger, REST APIs). * Experience with automation frameworks (Selenium, Playwright, PyTest). * Proficiency in Python. * Understanding of AI evaluation ...

Techvilla Solutions

$43.25 - $57/hr

Familiarity with AI-assisted development tools is required, with an emphasis on independent ... testing, and validating generated code. * Document automation playbooks, Terraform modules ...

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Ai Automation Testing information

What is AI automation testing?

AI automation testing refers to the use of artificial intelligence technologies to automate the process of testing software applications. This approach enhances traditional automated testing by using machine learning and data analysis to identify test cases, detect defects, and optimize test coverage. AI-driven testing tools can adapt to changes in the application, reduce manual effort, and improve the accuracy and speed of testing processes. As a result, organizations can deliver higher-quality software more efficiently.

What are the key skills and qualifications needed to thrive as an AI automation testing professional?

To thrive as an AI Automation Testing professional, you need a solid understanding of software testing principles, programming languages (such as Python or Java), and AI/ML concepts, often supported by a degree in computer science or a related field. Familiarity with automation tools like Selenium, Appium, and AI-powered testing frameworks, as well as certifications like ISTQB, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in diagnosing issues and collaborating with development teams. These skills ensure the delivery of robust, efficient, and reliable AI-driven software products in a competitive technology landscape.

What are some common challenges faced by AI automation testing professionals when validating machine learning models?

AI Automation Testing professionals often encounter challenges such as ensuring that test cases comprehensively cover the unique behaviors of machine learning models, dealing with non-deterministic outputs, and handling large datasets efficiently. It's also common to face difficulties in setting up reliable test environments that simulate real-world data scenarios. Collaboration with data scientists and developers is crucial to define meaningful metrics and effectively interpret test results, ensuring the AI system meets both functional and ethical standards.

What is the difference between Ai Automation Testing vs Software Test Engineer?

AspectAi Automation TestingSoftware Test Engineer
Required CredentialsCertifications in AI, automation tools, programming languagesSoftware testing certifications (ISTQB, CSTE), programming skills
Work EnvironmentFocus on automation frameworks, AI integration, scriptingManual and automated testing, test case design, bug tracking
Employer & Industry UsageTech companies, AI-driven projects, software development firmsSoftware development companies, IT departments, QA teams

Ai Automation Testing and Software Test Engineer roles overlap in testing skills and programming knowledge. However, Ai Automation Testing emphasizes AI integration and automation frameworks, while Software Test Engineers focus more on manual testing, test case creation, and bug identification. Both roles are essential in software quality assurance but serve different aspects of the testing process.

How to become an AI automation tester?

To become an AI automation tester, you should have a strong understanding of software testing principles, programming languages such as Python or Java, and experience with automation tools like Selenium or TestComplete. Familiarity with AI and machine learning concepts can be beneficial, along with certifications in testing or automation. Gaining hands-on experience through internships or projects is also valuable for this role.

Is AI automation testing a good career?

AI automation testing is a growing field within software quality assurance that involves using AI tools and scripting to automate test cases, increasing efficiency and coverage. It requires knowledge of programming, testing frameworks, and AI concepts, making it a valuable skill set with strong job prospects and competitive salaries.

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Ai Automation Testing jobs near you

Engineer, FW & Product Test Engineering - Micron Technology

Longmont, CO • On-site

Polluxa, Inc.
See more jobs at Polluxa, Inc.external

$100 - $125/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Our vision is to transform how the world uses information to enrich life for all .


Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.


We develop technologies that power the world's most advanced memory and storage solutions. The Firmware & Product Test (FPT) team plays a critical role in ensuring enterprise SSD firmware delivers the reliability, performance, and quality our customers depend on. By combining automation, data-driven testing, and emerging AI capabilities, we are continuously improving how firmware is validated and delivered.


As an Engineer II, you will help validate enterprise SSD firmware through test development, automation, execution, and failure analysis. This role offers the opportunity to work with NVMe technologies, AI-enabled engineering tools, and machine learning concepts while collaborating with experienced firmware engineers, mentors, and data scientists. Your contributions will help improve testing efficiency, scalability, and product quality.


Responsibilities:

  • Develop and implement firmware verification plans for customer requirements and NVMe features, including SMART, Trim, Get Log Page, and OCP

  • Design and implement test methodologies to validate firmware functionality and reliability

  • Analyze regression failures, perform root-cause analysis, and document findings and mitigation plans

  • Develop and enhance Python-based test automation, reporting, and data-collection tools within established validation frameworks

  • Leverage AI-powered tools and machine learning techniques to improve test efficiency, failure detection, and validation workflows


Minimum Qualifications:

  • Bachelor’s degree with approximately 3 years of relevant experience, or Master’s degree, in Computer Science, Data Science, Electrical Engineering, Computer Engineering, or a related field

  • Proficiency in Python and experience with libraries such as NumPy, pandas, and Scikit-learn

  • Experience with test automation, testing methodologies, validation tools, and debugging complex technical issues

  • Working knowledge of machine learning fundamentals, including algorithms, training concepts, and evaluation metrics

  • Experience using AI-powered tools or AI-enabled workflows to improve engineering productivity and test quality


Preferred Qualifications:

  • Experience with machine learning frameworks such as TensorFlow or PyTorch

  • Academic, research, or project experience in machine learning, data science, or artificial intelligence

  • Experience using AI-assisted development tools such as GitHub Copilot, Microsoft Copilot, Claude, or similar technologies

  • Understanding of embedded systems, firmware validation, or hardware testing concepts

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