Machine Learning Visa Sponsorship Jobs in Texas
Texas is one of the most active states for machine learning hiring, with major employers including Google, Meta, Amazon, and Dell Technologies operating across Austin, Dallas, and Houston. The state's fast-growing tech corridor and energy sector create consistent demand for ML engineers and researchers who need visa sponsorship.
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Get Access To All JobsPrincipal Machine Learning Engineer (MLE)
- JR-161164
- Hybrid
- Toronto
- Dallas
- Technology
- Full time
Who are we?
Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.
A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.
Job Summary
As a Principal Machine Learning Engineer, you will design, build, deploy, and scale machine learning and generative AI systems that power real-world products. You will work closely in AI Sidekick team and business teams to translate advanced ML and LLM capabilities into reliable, production-grade solutions across multi-cloud environments including GCP, AWS, and Azure. This role blends applied machine learning, software engineering, and MLOps, with a strong focus on building robust, scalable systems rather than purely academic research.
Responsibilities
- Design, develop, and deploy machine learning and Large Language Model (LLM)–based solutions for production use cases
- Collaborate with Generative AI Center of Excellence leaders and business stakeholders to evaluate buy vs. build decisions for generative AI applications
- Develop end-to-end ML pipelines, covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
- Architect and implement LLM-powered systems that integrate agents and services across multiple cloud platforms into a unified solution
- Optimize ML workflows for performance, scalability, reliability, and cost efficiency in cloud environments (GCP, Azure, AWS)
- Implement and maintain MLOps best practices, including CI/CD, model versioning, experiment tracking, and automated retraining
- Work extensively with deep learning frameworks such as PyTorch and TensorFlow
- Containerize ML services and deploy them using Docker, Kubernetes, App Engine, or virtual machines
- Apply strong knowledge of NLP fundamentals, including transformers, attention mechanisms, embeddings, and text preprocessing
- Deploy and manage models in production, conduct A/B testing, and measure performance improvements using statistical methods
- Develop features, run experiments, analyze results, and translate insights into actionable improvements
- Build and deploy classical ML models (regression, classification, clustering), NLP applications (sentiment analysis, summarization, Q&A, chatbots, information retrieval), and computer vision solutions (image classification, object detection, segmentation using models such as YOLOv7, DDRNet, RFTM with datasets like COCO and Cityscapes)
Qualifications
- PhD with 5+ years, Master’s with 6+ years, or Bachelor’s with 7+ years of experience in Machine Learning, Computer Science, Data Science, or a related field
- Strong proficiency in Python for machine learning and production systems
- Solid understanding of software engineering fundamentals, system design, and design patterns
- Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
- Experience building and deploying production-grade ML systems
- Strong communication skills with the ability to explain technical concepts and results to both technical and non-technical stakeholders
- Excellent time management, collaboration, and organizational skills
The targeted pay range for this position in the following location is / locations are:
Canada - Toronto Office TRO : 154,000 - 232,000 CAD / Annual
United States - Dallas Infomart Office DAI : 200,000 - 300,000 USD / Annual
Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location. The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience, and relevant education and/or training.
The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.
Equinix Benefits
As an employee, you become important to Equinix’s success. We ensure all your benefits are in line with our core values: competitive, inclusive, sustainable, connected and efficient. We keep them competitive within the current marketplace to ensure we’re providing you with the best package possible. So, wherever you are in your career and life, you’ll be able to enhance your experience and bring your whole self to work.
Employee Assistance Program: An Employee Assistance program is available to all employees.
US Benefits:
- Insurance: You may enroll in health, life, disability and voluntary plans that are designed for you and your eligible family members.
- Retirement: You and Equinix may contribute to a retirement plan to help you plan for your financial future.
- Paid Time Off (PTO) and Paid Holidays: You will receive an accrued amount of PTO each pay period along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to change and may be subject to specific plan or program terms.
Canada Core Benefits:
- Insurance: You may enroll in healthcare coverage that is designed to complement the provincial healthcare system, along with life, disability and optional benefit plans that are designed for you and your eligible family members.
- Retirement: You may also enroll in Equinix-sponsored retirement or savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP) and Tax-Free Savings Plan (TSFA).
- Vacation and Paid Holidays: Equinix offers both vacation and personal time, along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to specific plan or program terms, and to change at Equinix discretion.
Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing form.
Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.
We use artificial intelligence in our hiring process. Learn more here.
This posting is a new position within our organization.
Principal Machine Learning Engineer (MLE)
- JR-161164
- Hybrid
- Toronto
- Dallas
- Technology
- Full time
Who are we?
Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.
A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.
Job Summary
As a Principal Machine Learning Engineer, you will design, build, deploy, and scale machine learning and generative AI systems that power real-world products. You will work closely in AI Sidekick team and business teams to translate advanced ML and LLM capabilities into reliable, production-grade solutions across multi-cloud environments including GCP, AWS, and Azure. This role blends applied machine learning, software engineering, and MLOps, with a strong focus on building robust, scalable systems rather than purely academic research.
Responsibilities
- Design, develop, and deploy machine learning and Large Language Model (LLM)–based solutions for production use cases
- Collaborate with Generative AI Center of Excellence leaders and business stakeholders to evaluate buy vs. build decisions for generative AI applications
- Develop end-to-end ML pipelines, covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
- Architect and implement LLM-powered systems that integrate agents and services across multiple cloud platforms into a unified solution
- Optimize ML workflows for performance, scalability, reliability, and cost efficiency in cloud environments (GCP, Azure, AWS)
- Implement and maintain MLOps best practices, including CI/CD, model versioning, experiment tracking, and automated retraining
- Work extensively with deep learning frameworks such as PyTorch and TensorFlow
- Containerize ML services and deploy them using Docker, Kubernetes, App Engine, or virtual machines
- Apply strong knowledge of NLP fundamentals, including transformers, attention mechanisms, embeddings, and text preprocessing
- Deploy and manage models in production, conduct A/B testing, and measure performance improvements using statistical methods
- Develop features, run experiments, analyze results, and translate insights into actionable improvements
- Build and deploy classical ML models (regression, classification, clustering), NLP applications (sentiment analysis, summarization, Q&A, chatbots, information retrieval), and computer vision solutions (image classification, object detection, segmentation using models such as YOLOv7, DDRNet, RFTM with datasets like COCO and Cityscapes)
Qualifications
- PhD with 5+ years, Master’s with 6+ years, or Bachelor’s with 7+ years of experience in Machine Learning, Computer Science, Data Science, or a related field
- Strong proficiency in Python for machine learning and production systems
- Solid understanding of software engineering fundamentals, system design, and design patterns
- Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
- Experience building and deploying production-grade ML systems
- Strong communication skills with the ability to explain technical concepts and results to both technical and non-technical stakeholders
- Excellent time management, collaboration, and organizational skills
The targeted pay range for this position in the following location is / locations are:
Canada - Toronto Office TRO : 154,000 - 232,000 CAD / Annual
United States - Dallas Infomart Office DAI : 200,000 - 300,000 USD / Annual
Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location. The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience, and relevant education and/or training.
The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.
Equinix Benefits
As an employee, you become important to Equinix’s success. We ensure all your benefits are in line with our core values: competitive, inclusive, sustainable, connected and efficient. We keep them competitive within the current marketplace to ensure we’re providing you with the best package possible. So, wherever you are in your career and life, you’ll be able to enhance your experience and bring your whole self to work.
Employee Assistance Program: An Employee Assistance program is available to all employees.
US Benefits:
- Insurance: You may enroll in health, life, disability and voluntary plans that are designed for you and your eligible family members.
- Retirement: You and Equinix may contribute to a retirement plan to help you plan for your financial future.
- Paid Time Off (PTO) and Paid Holidays: You will receive an accrued amount of PTO each pay period along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to change and may be subject to specific plan or program terms.
Canada Core Benefits:
- Insurance: You may enroll in healthcare coverage that is designed to complement the provincial healthcare system, along with life, disability and optional benefit plans that are designed for you and your eligible family members.
- Retirement: You may also enroll in Equinix-sponsored retirement or savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP) and Tax-Free Savings Plan (TSFA).
- Vacation and Paid Holidays: Equinix offers both vacation and personal time, along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to specific plan or program terms, and to change at Equinix discretion.
Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing form.
Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.
We use artificial intelligence in our hiring process. Learn more here.
This posting is a new position within our organization.
Machine Learning Job Roles in Texas
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Search Machine Learning Jobs in TexasMachine Learning Jobs in Texas: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in Texas?
Several large employers in Texas have established records of sponsoring work visas for machine learning talent. These include Google and Meta in Austin, AT&T and Goldman Sachs in Dallas, and ExxonMobil and Schlumberger in Houston, which apply ML to energy data problems. Large defense contractors such as Raytheon and Lockheed Martin also hire ML engineers in the Dallas-Fort Worth area, though some roles require U.S. citizenship.
Which visa types are most common for machine learning jobs in Texas?
The H-1B visa is the most common visa category for machine learning roles in Texas, as ML engineer and data scientist positions consistently qualify as specialty occupations requiring at least a bachelor's degree in computer science, statistics, or a related field. Candidates with extraordinary ability may pursue the O-1A. Australians working in ML may qualify for the E-3 visa, and Canadian and Mexican nationals may explore TN visa status under the USMCA mathematician or computer systems analyst categories.
Which cities in Texas have the most machine learning sponsorship jobs?
Austin concentrates the largest share of ML sponsorship opportunities in Texas, driven by a dense cluster of tech companies and the presence of UT Austin's strong computer science program. Dallas-Fort Worth is a close second, with significant activity in financial services, telecom, and defense. Houston adds meaningful volume through energy-sector applications of ML, particularly in predictive maintenance, seismic analysis, and supply chain optimization.
How to find machine learning visa sponsorship jobs in Texas?
Migrate Mate is built specifically for international job seekers and filters machine learning roles in Texas by visa sponsorship status, so you're only seeing employers actively open to sponsoring. You can filter by city, visa type, and role to narrow results quickly. Because ML is a high-demand field in Texas, new sponsored positions are posted regularly across Austin, Dallas, and Houston, making it worth checking Migrate Mate consistently rather than in a single session.
Are there any Texas-specific considerations for machine learning visa sponsorship?
Texas has no state income tax, which affects prevailing wage comparisons under H-1B Labor Condition Applications since take-home pay differs from states with income tax. The Department of Labor sets prevailing wages by metropolitan area, so rates in Austin, Dallas, and Houston each differ. UT Austin, Rice University, and Texas A&M produce significant ML research talent, meaning local university hiring pipelines are active and some roles are tied to research lab positions that carry their own visa sponsorship structures.
What is the prevailing wage for sponsored machine learning jobs in Texas?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.