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Google Machine Learning Engineer Jobs in Dallas, TX

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

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

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Machine Learning Engineer, Specialist

Dallas, TX

$113.30K - $136K/yr

Performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment. Leverages detailed understanding of ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

AI & Machine Learning Engineer

Dallas, TX

$113.70K - $136.60K/yr

... think Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Intel, Walmart Labs, Citi, JPMC ... engineer , data scientist , and machine learning/AI engineer . In other words, SynergisticIT ...

AI & Machine Learning Engineer

Dallas, TX

$113.70K - $136.60K/yr

... think Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Intel, Walmart Labs, Citi, JPMC ... engineer , data scientist , and machine learning/AI engineer . In other words, SynergisticIT ...

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Google Machine Learning Engineer information

See Dallas, TX salary details

$31.2K

$127.4K

$191.4K

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

As of May 29, 2026, the average yearly pay for google 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 is a Google Machine Learning Engineer job?

A Google Machine Learning Engineer designs, builds, and optimizes machine learning models to improve Google's products and services. They work with large datasets, implement algorithms, and deploy scalable AI systems. Collaboration with data scientists, software engineers, and product teams is essential to integrate models into real-world applications. Strong knowledge of Python, TensorFlow, and cloud computing is often required. This role focuses on both research and practical implementation to enhance automation and decision-making across Google products.

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

To thrive as a Google Machine Learning Engineer, you need strong expertise in mathematics, statistics, programming (especially Python or C++), and a solid background in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud), and advanced certifications can be highly beneficial. Excellent problem-solving, teamwork, and communication skills help you collaborate across teams and explain complex models to stakeholders. These skills are essential to driving innovation, building scalable solutions, and ensuring impactful results in a fast-paced, research-driven environment.

What types of projects and collaborations can Google Machine Learning Engineers expect to be involved in?

Google Machine Learning Engineers often contribute to diverse projects, such as developing next-generation search algorithms, optimizing user experiences across products, or creating scalable machine learning systems for internal and external clients. The role frequently involves collaborating with data scientists, product managers, software engineers, and researchers to define project goals and deliver impactful solutions. You can expect to participate in code reviews, prototype new models, and provide expert input during technical discussions. This collaborative, interdisciplinary approach ensures innovative outcomes and offers ongoing opportunities for professional growth and skill development.
What are popular job titles related to Google Machine Learning Engineer jobs in Dallas, TX? For Google Machine Learning Engineer jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Google Machine Learning Engineer jobs in Dallas, TX look for? The top searched job categories for Google Machine Learning Engineer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Google Machine Learning Engineer jobs? Cities near Dallas, TX with the most Google Machine Learning Engineer job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Capital One

Plano, TX • On-site, Remote

$100K - $137.30K/yr

Full-time

Posted 5 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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