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Machine Learning Qa Engineer Jobs (NOW HIRING)

Lancope

Quality Assurance Engineer

Alpharetta, GA · On-site

Active learning of product capabilities and customer needs * Work with QA leadership and other QA ... virtual machine environments (e.g. VMWare, KVM) * 2+ years of experience using test automation ...

Fastbreak AI

QA Engineer

Charlotte, NC · Hybrid

We're seeking a QA Engineer who brings both creative problem-solving and rock-solid testing ... Exposure to AI-powered testing tools or machine learning concepts in QA Location * We're based in ...

Fastbreak AI

QA Engineer

Charlotte, NC · On-site

We're seeking a QA Engineer who brings both creative problem-solving and rock-solid testing ... Exposure to AI‑powered testing tools or machine learning concepts in QA Location * We're based in ...

Siri InfoSolutions Inc

Lead QA Engineer

Charlotte, NC · On-site

$126K/yr

Role: QA Engineer Location: Charlotte, NC Duration: Full time Primary Skill : Test AI applications ... Design end-to-end test plans for generative AI, LLMs, and machine learning models. * Model ...

New

Rectangle Health

QA Engineer

White Plains, NY · On-site

$90K - $115K/yr

QA Engineer At Rectangle Health, we believe that our team members are our most important asset. We ... Receptive to feedback and committed to continuous learning and growth. Compensation & Benefits ...

Rectangle Health

QA Engineer

White Plains, NY · On-site

$90K - $115K/yr

QA Engineer At Rectangle Health, we believe that our team members are our most important asset. We ... Receptive to feedback and committed to continuous learning and growth. Compensation & Benefits ...

Alliance Industries Inc

QA Engineer

Marietta, OH · On-site

TERRA SONIC - Quality Assurance Engineer The QA Engineer at Terra Sonic International maintains a ... They work side by side with machinists, fabricators, assembly personnel, and Manufacturing ...

Inceed

QA Engineer

Kansas City, MO · On-site

$45 - $54/hr

Weekly direct deposit or pay card deposit If you are interested in learning more about the QA Engineer opportunity, please submit your resume for consideration. Our client unable to provide ...

Arbitersports

Quality Assurance Engineer

We are seeking a curious, analytical, and continuously learning Quality Assurance Engineer. In this role, you will leverage AI powered tools to contribute throughout the development lifecycle ...

Alliance Industries

QA Engineer

Marietta, OH · On-site

Technical Marietta, OH, US 3 days ago Requisition ID: 1572 TERRA SONIC - Quality Assurance Engineer ... They work side by side with machinists, fabricators, assembly personnel, and Manufacturing ...

Brilent

QA Engineer Intern

San Mateo, CA · On-site

The Brilent team brings together deep experience in machine learning, and data science from leading ... As a QA Engineer Intern, you will work alongside our small team of engineers to develop new ...

Komatsu

Quality Assurance Engineer

Peoria, IL · On-site

$76K - $95K/yr

Review and analyze all TSI and ETSI submitted in Peoria manufactured machines. Organize the data ... Employee learning and development programs Diversity & Inclusion Commitment At Komatsu, we come ...

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Machine Learning QA Engineer information

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How much do machine learning qa engineer jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for machine learning qa engineer in the United States is $48.54, according to ZipRecruiter salary data. Most workers in this role earn between $38.22 and $55.53 per hour, depending on experience, location, and employer.

What is a machine learning QA engineer?

Machine Learning QA Engineers are professionals who specialize in testing and validating machine learning models and systems. They ensure that machine learning algorithms perform as expected, are reliable, and meet quality standards before deployment. Their role involves developing test cases, automating testing processes, analyzing results, and collaborating with data scientists and software engineers to improve model accuracy and robustness. They also help identify biases, data inconsistencies, and potential issues in the machine learning pipeline.

What are some common challenges faced by machine learning QA engineers when testing AI models, and how are they typically addressed?

Machine Learning QA Engineers often encounter challenges such as ensuring model accuracy across diverse datasets, reproducibility of test results, and validating the fairness and bias of AI outputs. Addressing these issues typically involves developing robust automated test frameworks, collaborating closely with data scientists to understand model behaviors, and implementing rigorous data validation and monitoring processes. Additionally, continuous learning is essential, as ML models evolve rapidly and require QA Engineers to stay updated on new testing methodologies and tools.

What are the key skills and qualifications needed to thrive as a machine learning QA engineer, and why are they important?

To thrive as a Machine Learning QA Engineer, you need a strong grasp of software testing principles, machine learning concepts, and proficiency in programming languages like Python, along with a relevant degree in computer science or engineering. Familiarity with testing frameworks (such as pytest), ML platforms (like TensorFlow or PyTorch), and experience with automated testing tools are typically required. Exceptional analytical thinking, attention to detail, and effective communication skills set standout candidates apart in this role. These skills and qualities are crucial to ensure the quality, reliability, and fairness of machine learning models before they are deployed to production.

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

AspectMachine Learning Qa EngineerData Scientist
Required CredentialsBachelor's in CS, QA certifications, knowledge of ML modelsBachelor's/Master's in CS, statistics, data analysis
Work EnvironmentTesting labs, development teams, QA departmentsResearch, data analysis, modeling teams
Industry UsageTech companies, AI startups, software firmsTech, finance, healthcare, research institutions
Common Search/ComparisonYesYes

While both roles involve working with machine learning, a Machine Learning Qa Engineer primarily focuses on testing and validating ML models to ensure quality and performance. In contrast, a Data Scientist analyzes data, develops models, and derives insights. The roles often collaborate but serve different stages of the ML development lifecycle.

Is a machine learning QA engineer still in demand?

Machine Learning QA engineers are in demand due to the increasing adoption of AI and machine learning systems across industries. They play a critical role in testing and validating models, often requiring skills in programming, data analysis, and familiarity with tools like Python and TensorFlow. As AI integration grows, the need for specialized QA engineers in this field is expected to remain strong.
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Infographic showing various Machine Learning Qa Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $100,970 per year, or $48.5 per hour.

Machine Learning Engineer, Software QA - Creativity Apps

San Diego, CA • On-site

Apple
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Appleexternal

Full-time

Posted 21 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 684 frontline employees who took The Breakroom Quiz

Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
The Creativity Apps QA team is seeking a Software QA Engineer, Machine Learning to help us ensure that our iOS and macOS creativity applications are high-quality. We're looking for an engineer to take projects from defining evaluation strategy, evaluation scripting and automation, leading all stages of testing, triaging and driving issues to resolution, and ensuring high quality models are integrated into our Apps' clients through rigorous testing methodologies. You will have the unique and rewarding opportunity to help shape upcoming products that will delight and inspire millions of Apple's customers every day.
Description
This position requires a self-motivated individual with strong technical, problem solving and communication skills, and the willingness to work in a sophisticated environment. Responsibilities include scripting, parsing data, and working closely with the annotation operations team. Analyzing annotations and test results to ensure the features work end-to-end for customers. Developing and implementing workflow projects, regression testing, and bug filing. You will work closely with other team members to develop requirements, identify appropriate testing implementations processes, and methodologies. You should be able to be comfortable with ambiguity and make educated, critical judgments. You must be effective and systematic at managing priorities, and communicating progress as well as risk through regular status updates. Have a proven ability to ramp up quickly on both existing and new technologies.
Minimum Qualifications
At least 5 years industry experience ideally in quality assurance with a prior focus in Machine Learning.
Strong comprehension of machine learning algorithms, supervised and unsupervised modeling techniques.
Understand of the mechanics of machine learning, deep learning, computer vision, natural language processing, and generative AI.
Proficient in Python and/or Swift or comparable languages.
Preparing and collecting data for evaluation and ensuring data quality.
Meticulous, analytical, methodical and creative problem solving ability with a commitment to driving quality forward.
Detail-oriented, analytical, methodical and creative thinker committed to driving quality forward.
Prototyping and tools development experience.
Strong presentation skills and ability to adapt technical presentation to various audiences.
Proficiency in utilizing LLMs and Generative AI frameworks to automate model evaluation processes, optimize test execution times, and improve evaluation accuracy and efficiency.
Bachelor's degree in Computer Science, Data Science, Applied Mathematics or similar, combined with an understanding of SQA methodologies, machine learning and software engineering experience.
Preferred Qualifications
Understanding of subjective/objective image and video quality evaluation, and color science concepts is a strong plus.
Understanding of SQA methodologies and practices, software engineering experience preferred.
iOS and macOS familiarity.

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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