Machine Learning Engineer Jobs in Texas
Machine Learning Engineer jobs in Texas are highly active, with strong demand across technology, energy, financial services, and defense sectors at levels from entry-level to principal engineer. Austin, Dallas, and Houston anchor most of the hiring, where established employers such as Dell Technologies, JPMorgan Chase, and Raytheon Technologies maintain large technical teams. The most sought-after specialties in Texas include natural language processing, computer vision, and MLOps infrastructure. Find a role that fits below and apply directly.
Find JobsOverview
Showing 5 of 117+ Machine Learning Engineer jobs
At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew.
We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.
To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.
Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.
If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you.
WHAT YOU'LL DO
Braze is seeking a Staff Machine Learning Engineer to join our Predictive and Generative AI (PGAI) team. The team's mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions. We run those solutions as production systems at global scale, from the distributed pipelines that train models for each customer to the high-throughput APIs that serve predictions into our messaging systems across multiple regions. You will own the platform underneath, and you will make deploying, operating, and scaling ML at Braze fast, safe, and efficient.
As the Staff Engineer on the team, you will:
- Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure
- Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely
- Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale
- Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams
- Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists
- Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership
WHO YOU ARE
- 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load
- Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement
- A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
- Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run
- An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making
- Bonus:
- Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- ML platform tooling such as MLflow or another model registry, feature stores, or ML observability
- Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
- Operating under compliance regimes such as SOX or HIPAA
- Customer engagement, personalization, or marketing technology domain experience
For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.
#LI-Hybrid
WHAT WE OFFER
Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here. More details on benefits plans will be provided if you receive an offer of employment.
From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as:
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
- A curated in-office employee experience, designed to foster community, team connections, and innovation
- Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
- Employee Resource Groups that provide supportive communities within Braze
- Collaborative, transparent, and fun culture recognized as a Great Place to Work®
ABOUT BRAZE
Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.™ Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI™ allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences.
The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 "Best of Marketing and Digital Advertising Software Product" in 2025.
Braze was also named a 2025 Best Companies To Work For by U.S. News & World Report, a 2025 America's Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology™ by Great Place To Work®, among other accolades. Braze is also proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore.
The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo.
BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER
At Braze, we strive to create equitable growth and opportunities inside and outside the organization.
Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience – regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you.
We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we'd love to meet you
OUR AI-POWERED BRAZE RECRUITMENT PROCESS
At Braze, we're committed to a fair and transparent candidate experience. To help our recruitment teams focus on what matters most — the person behind each application — we use AI-assisted tools at certain stages of our recruitment process.
This includes using AI to analyze the experience, skills and qualifications in your application materials to help with screening and prioritizing candidates. Such screening may amount to a form of solely automated decision-making. We also use AI for administrative support, like scheduling and recording interviews and summarizing interview notes. Our recruiting teams remain responsible for all hiring decisions and are involved throughout the process.
Depending on where you are located, you may have certain rights available to you in relation to Braze's use of AI:
- To opt out of AI-assisted review of your application, please click the "Learn More" at the end of the application form below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application.
- To exercise other types of rights, such as rights to request further information about how AI is used in our recruitment process, to request a manual review of any decision made or to contest a decision, please contact us at talentdata.privacy@braze.com.
Please contact us at talentdata.privacy@braze.com with any questions. To find out more about our hiring process, check out this page.
Notice Regarding Automated Employment Decision Tool (NYC Local Law 144)
Our use of AI during the application review process may include the use of automated employment decision tools. Pursuant to New York City Local Law 144, for roles based in New York City, or if you reside in New York City, you have the right to request an alternative selection process or a reasonable accommodation instead of AI-assisted review.
To opt out of AI-assisted review of your application, please click the "Learn More" button below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application. Please submit any other request to our Talent Acquisition team at talentdata.privacy@braze.com promptly after applying. Summaries of the most recent bias audit results for such tools are available here.
Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.
At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew.
We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.
To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.
Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.
If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you.
WHAT YOU'LL DO
Braze is seeking a Staff Machine Learning Engineer to join our Predictive and Generative AI (PGAI) team. The team's mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions. We run those solutions as production systems at global scale, from the distributed pipelines that train models for each customer to the high-throughput APIs that serve predictions into our messaging systems across multiple regions. You will own the platform underneath, and you will make deploying, operating, and scaling ML at Braze fast, safe, and efficient.
As the Staff Engineer on the team, you will:
- Identify and drive the transformative initiatives that change how the team runs ML in production, whether that's replatforming our queueing and orchestration, overhauling deployment and cloud identity, or retiring a generation of infrastructure
- Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex infrastructure initiatives yourself from design through production. Current examples include multi-region model serving fleets, the pipelines that keep hundreds of customer-specific models healthy, and the CI and deployment tooling that moves it all safely
- Own the platform's technical vision and production quality bar. Set direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive the reliability and cost work that keeps the platform efficient at scale
- Drive initiatives that span teams. Our platform builds on shared infrastructure, deployment tooling, and data systems owned with partner teams, and you carry the technical relationships with those teams
- Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists
- Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership
WHO YOU ARE
- 8+ years building and operating distributed systems in production, with depth in deployment and operations. You have designed services for scale and reliability, owned CI/CD and infrastructure as code, and run what you built under production load
- Hands-on experience with ML workloads in production. Training pipelines, model serving, feature systems, or ML platform tooling all count; deep modeling experience is a plus rather than a requirement
- A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
- Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of what you run
- An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making
- Bonus:
- Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- ML platform tooling such as MLflow or another model registry, feature stores, or ML observability
- Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
- Operating under compliance regimes such as SOX or HIPAA
- Customer engagement, personalization, or marketing technology domain experience
For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $314,000/year, with an expected On Target Earnings (OTE) between $204,000 and $348,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.
#LI-Hybrid
WHAT WE OFFER
Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here. More details on benefits plans will be provided if you receive an offer of employment.
From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as:
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
- A curated in-office employee experience, designed to foster community, team connections, and innovation
- Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
- Employee Resource Groups that provide supportive communities within Braze
- Collaborative, transparent, and fun culture recognized as a Great Place to Work®
ABOUT BRAZE
Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.™ Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI™ allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences.
The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 "Best of Marketing and Digital Advertising Software Product" in 2025.
Braze was also named a 2025 Best Companies To Work For by U.S. News & World Report, a 2025 America's Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology™ by Great Place To Work®, among other accolades. Braze is also proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore.
The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo.
BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER
At Braze, we strive to create equitable growth and opportunities inside and outside the organization.
Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience – regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you.
We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we'd love to meet you
OUR AI-POWERED BRAZE RECRUITMENT PROCESS
At Braze, we're committed to a fair and transparent candidate experience. To help our recruitment teams focus on what matters most — the person behind each application — we use AI-assisted tools at certain stages of our recruitment process.
This includes using AI to analyze the experience, skills and qualifications in your application materials to help with screening and prioritizing candidates. Such screening may amount to a form of solely automated decision-making. We also use AI for administrative support, like scheduling and recording interviews and summarizing interview notes. Our recruiting teams remain responsible for all hiring decisions and are involved throughout the process.
Depending on where you are located, you may have certain rights available to you in relation to Braze's use of AI:
- To opt out of AI-assisted review of your application, please click the "Learn More" at the end of the application form below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application.
- To exercise other types of rights, such as rights to request further information about how AI is used in our recruitment process, to request a manual review of any decision made or to contest a decision, please contact us at talentdata.privacy@braze.com.
Please contact us at talentdata.privacy@braze.com with any questions. To find out more about our hiring process, check out this page.
Notice Regarding Automated Employment Decision Tool (NYC Local Law 144)
Our use of AI during the application review process may include the use of automated employment decision tools. Pursuant to New York City Local Law 144, for roles based in New York City, or if you reside in New York City, you have the right to request an alternative selection process or a reasonable accommodation instead of AI-assisted review.
To opt out of AI-assisted review of your application, please click the "Learn More" button below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application. Please submit any other request to our Talent Acquisition team at talentdata.privacy@braze.com promptly after applying. Summaries of the most recent bias audit results for such tools are available here.
Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.
See All 117+ Machine Learning Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find JobsMachine Learning Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Machine Learning Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
- Amazon Web Services31
- Apple10
- General Motors4
- Striveworks3
- JPMorganChase3
Top Industries Hiring
- Electronics & Hardware12
- Technology & Software6
- Banking & Financial Services5
- Automotive4
- Education2
What Texas Employers Look For
The qualifications that appear most often in machine learning engineer jobs across Texas.
- Bachelor's or master's degree in computer science, statistics, or a related engineering field
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Hands-on experience building, training, and deploying machine learning models in production environments
- Familiarity with cloud platforms including AWS, Google Cloud, or Microsoft Azure for ML workloads
- Strong understanding of data pipelines, feature engineering, and model evaluation methodologies
- Experience with MLOps practices including model versioning, monitoring, and CI/CD for ML systems
Machine Learning Engineer Jobs in Texas: Frequently Asked Questions
How do you become a machine learning engineer in Texas?
Machine learning engineering in Texas has no state-issued license or registration requirement, so the path centers on education and demonstrated skills. Most Texas employers expect at least a bachelor's degree in computer science, mathematics, or a related field, with a master's degree preferred for senior positions. Building a strong project portfolio, contributing to open-source ML projects, and earning cloud certifications from AWS or Google Cloud are concrete steps that accelerate hiring in the Texas market.
How much do machine learning engineers make in Texas?
Machine learning engineers in Texas earn a median of about $132,150 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $82,600 for the lowest 10% to over $183,680 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire machine learning engineers in Texas?
Employers hiring machine learning engineers in Texas right now include Amazon Web Services, Apple, and General Motors, based on current listings on Migrate Mate as of September 2026. Texas's concentration of technology campuses, financial institutions, and defense contractors means demand is distributed across multiple industries rather than limited to pure software companies.
Which Texas cities have the most machine learning engineer jobs?
Austin, Houston, and Plano have the most machine learning engineer openings in Texas. Austin's dense technology sector drives the bulk of listings, while Dallas benefits from a large concentration of financial services and enterprise technology headquarters, and Houston's energy and aerospace industries generate consistent demand for applied ML talent.
Are there remote machine learning engineer jobs in Texas?
Yes, and more than most fields. Machine learning engineering is highly amenable to remote work given its desk-based, analytical nature. About 68% of machine learning engineer openings tied to Texas are remote or hybrid as of September 2026, reflecting how widely distributed ML teams have become. Model development, experimentation, and data pipeline work are the functions most commonly performed fully remote.
How can I get hired as a machine learning engineer in Texas with little or no experience?
The most realistic entry path is landing a data analyst or junior data scientist role first, then transitioning into ML engineering as you build model-building experience. Large Texas employers such as Dell Technologies, AT&T, and major financial institutions in Dallas run associate and rotational technology programs that accept recent graduates. A portfolio of end-to-end projects on GitHub, a cloud certification, and familiarity with SQL and Python are the credentials that most consistently open doors for candidates without formal ML experience.
Where can I find and apply to machine learning engineer jobs in Texas?
You can find and apply to machine learning engineer jobs in Texas on Migrate Mate, which lists current Texas openings across industries and experience levels. Find the roles that fit your background and apply directly to each one.
See All 117+ Machine Learning Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find Jobs