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Mlops Machine Learning Engineer Jobs in Dallas, TX

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Machine Learning Developer

Dallas, TX · On-site

$140 - $190/hr

The Machine Learning (ML) Developer is the first dedicated ML Development role in the department ... Establish the department's MLOps standards, reusable pipeline patterns, and "golden path" for ...

... the machine learning function at a market-leading insurance company. As one of the first data ... Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $130K/yr

Lead 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 ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/yr

Lead 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 ...

R249230Lead Machine Learning Engineer**Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $130K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Showing results 21-40

Mlops Machine Learning Engineer information

See Dallas, TX salary details

$31.2K

$127.4K

$191.4K

How much do mlops machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for mlops machine learning engineer in Dallas, TX is $127,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What job categories do people searching Mlops Machine Learning Engineer jobs in Dallas, TX look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Mlops Machine Learning Engineer jobs?

Cities near Dallas, TX with the most Mlops Machine Learning Engineer job openings:

Distinguished Machine Learning Engineer

Capital One

Plano, TX • On-site, Remote

Full-time

Re-posted 23 days ago


Key responsibilities

  • Deliver ML models and software components that solve challenging business problems in the financial services industry.

  • Lead large-scale ML initiatives with the customer in mind.

  • Optimize data pipelines to feed ML models.


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 148 frontline employees who took The Breakroom Quiz

89th of 175 rated banks


Job description

Distinguished Machine Learning Engineer

Overview:

As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams 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 serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring 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. You'll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.

What you'll do in the role:

  • Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams

  • Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems

  • Lead large-scale ML initiatives with the customer in mind

  • Leverage cloud-based architectures and technologies to deliver optimized ML models at scale

  • Optimize data pipelines to feed ML models

  • Evangelize best practices in all aspects of the engineering and modeling lifecycles

  • Help recruit, nurture, and retain top engineering talent

Basic Qualifications:

  • Bachelor's degree

  • At least 10 years of experience designing and building data-intensive solutions using distributed computing

  • At least 6 years of experience programming in C, C++, Python, or Scala

  • At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting

Preferred Qualifications:

  • Master's Degree

  • 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models

  • 2+ years of experience using Dask, RAPIDS, or in High Performance Computing

  • 2+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)

  • Ability to communicate complex technical concepts clearly to a variety of audiences

  • ML industry impact through conference presentations, papers, blog posts, or open source contributions

  • Ability to attract and develop high-performing software engineers with an inspiring leadership style

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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.

McLean, VA: $269,100 - $307,200 for Distinguished Machine Learning Engineer


Plano, TX: $244,700 - $279,200 for Distinguished 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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