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Machine Learning Testing Jobs in Texas (NOW HIRING)

Senior Machine Learning Engineer

Plano, TX · On-site +1

$100K - $137.30K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Solve complex problems by writing and testing application code, developing and validating ML models ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98.10K - $129.20K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Solve complex problems by writing and testing application code, developing and validating ML models ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121.40K - $160.10K/yr

... and testing workflows. Bachelor's degree in Computer Science, Statistics, Mathematics with equivalent experience.5+ years of related experience building high throughput scalable applications or ...

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data ... Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate ...

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data ... Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate ...

Machine Learning Engineer, Specialist

Dallas, TX

$113.30K - $136K/yr

... adversarial testing service. We're looking for people who are technically sharp and effective ... Performs the development and programming of machine learning integrated software algorithms to ...

Senior Machine Learning Engineer

Houston, TX

$117K - $154.20K/yr

... testing, and code review * 5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154.20K/yr

... testing, and code review * 5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production ...

Senior Machine Learning Engineer

Houston, TX

$117K - $154.20K/yr

... testing, and code review * 5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production ...

Senior Machine Learning Engineer

Austin, TX · On-site

$181.10K - $318.40K/yr

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121.40K - $160.10K/yr

... testing. You will also work on building out a SOTA machine learning platform. We're looking for strong engineers well versed with modern large scale machine learning platforms with a solid grasp of ...

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

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Machine Learning Testing information

See Texas salary details

$12

$21

$28

How much do machine learning testing jobs pay per hour?

As of May 30, 2026, the average hourly pay for machine learning testing in Texas is $21.26, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $23.75 per hour, depending on experience, location, and employer.

What is a Machine Learning Testing job?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

What are the key skills and qualifications needed to thrive in the Machine Learning Testing position, and why are they important?

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

What are the typical challenges faced by professionals in Machine Learning Testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.
What are the most commonly searched types of Machine Learning Testing jobs in Texas? The most popular types of Machine Learning Testing jobs in Texas are:
Infographic showing various Machine Learning Testing job openings in Texas as of May 2026, with employment types broken down into 3% As Needed, 82% Full Time, 10% Part Time, 3% Contract, and 2% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $44,224 per year, or $21.3 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Capital One

Plano, TX • On-site, Remote

$100K - $137.30K/yr

Full-time

Posted 6 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

74th of 141 rated banks


Job description

Senior Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you'll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.

  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).

  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.

  • Retrain, maintain, and monitor models in production.

  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

  • Construct optimized data pipelines to feed ML models.

  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.

  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

  • Use programming languages like Python, Scala, or Java.

Basic Qualifications:

  • Bachelor's Degree

  • At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)

  • At least 3 years of experience designing and building data-intensive solutions using distributed computing

  • At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)

  • At least 1 year of experience productionizing, monitoring, and maintaining models

Preferred Qualifications:

  • 1+ years of experience building, scaling, and optimizing ML systems

  • 1+ years of experience with data gathering and preparation for ML models

  • 2+ years of experience developing performant, resilient, and maintainable code

  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field

  • 3+ years of experience with distributed file systems or multi-node database paradigms

  • Contributed to open source ML software

  • Authored/co-authored a paper on a ML technique, model, or proof of concept

  • 3+ years of experience building production-ready data pipelines that feed ML models

  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Chicago, IL: $147,100 - $167,900 for Senior Machine Learning Engineer


McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer


Plano, TX: $147,100 - $167,900 for Senior Machine Learning Engineer


Richmond, VA: $147,100 - $167,900 for Senior Machine Learning Engineer








Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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