Applied Scientist Jobs in Texas
Applied Scientist jobs in Texas are among the most active in the country, concentrated in machine learning, natural language processing, and statistical modeling across technology, aerospace, energy, and healthcare sectors, with openings at every level from entry-level researcher through principal and staff scientist. Austin, Dallas, and Houston anchor most of the hiring, where established employers like Amazon, Meta, and ExxonMobil maintain large technical operations and research functions. Demand is especially strong in generative AI applications, recommendation systems, and applied ML for industrial and energy forecasting. Find a role that fits below and apply directly.
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DESCRIPTION
We are looking for an AI/ML Engineer to build efficient, stable foundation models for long-horizon agentic workloads. The role combines model development with systems and hardware optimization.
Qualifications
Strong background in machine learning, deep learning, transformers, and foundation models.
Experience with PyTorch, JAX, or similar frameworks.
Experience training, fine-tuning, or serving large-scale models.
Knowledge of GPU architecture, CUDA, Triton, custom kernels, or hardware-aware optimization.
Familiarity with distributed training and model parallelism.
Experience with AWS Trainium, Inferentia, Neuron SDK, TPUs, or other custom accelerators is preferred.
PhD in machine learning, computer science, electrical engineering, or a related field is preferred.
Key job responsibilities
Responsibilities
Design, train, fine-tune, and evaluate custom foundation models.
Improve model efficiency, stability, latency, throughput, and memory usage.
Build models that support planning, tool use, memory, self-correction, and multi-step task execution.
Optimize training and inference using CUDA, Triton, custom GPU kernels, and tensor operations.
Profile and resolve compute, memory, communication, and distributed-training bottlenecks.
Work with GPUs and specialized AI accelerators, including AWS Trainium and other custom tensor hardware.
Develop evaluations for model reliability and long-horizon agent performance.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Houston - 142,800.00 - 193,200.00 USD annually
DESCRIPTION
We are looking for an AI/ML Engineer to build efficient, stable foundation models for long-horizon agentic workloads. The role combines model development with systems and hardware optimization.
Qualifications
Strong background in machine learning, deep learning, transformers, and foundation models.
Experience with PyTorch, JAX, or similar frameworks.
Experience training, fine-tuning, or serving large-scale models.
Knowledge of GPU architecture, CUDA, Triton, custom kernels, or hardware-aware optimization.
Familiarity with distributed training and model parallelism.
Experience with AWS Trainium, Inferentia, Neuron SDK, TPUs, or other custom accelerators is preferred.
PhD in machine learning, computer science, electrical engineering, or a related field is preferred.
Key job responsibilities
Responsibilities
Design, train, fine-tune, and evaluate custom foundation models.
Improve model efficiency, stability, latency, throughput, and memory usage.
Build models that support planning, tool use, memory, self-correction, and multi-step task execution.
Optimize training and inference using CUDA, Triton, custom GPU kernels, and tensor operations.
Profile and resolve compute, memory, communication, and distributed-training bottlenecks.
Work with GPUs and specialized AI accelerators, including AWS Trainium and other custom tensor hardware.
Develop evaluations for model reliability and long-horizon agent performance.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Houston - 142,800.00 - 193,200.00 USD annually
See All 10 Applied Scientist Jobs in Texas
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Find Applied Scientist JobsApplied Scientist Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Applied Scientist Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Distribution & Wholesale
- Retail
- Electronics & Hardware
- E-Commerce & Online Marketplaces
What Texas Employers Look For
The qualifications that appear most often in applied scientist jobs across Texas.
- Master's or PhD in computer science, statistics, or a related quantitative field
- Proficiency in Python, R, or Scala with demonstrated experience building production ML models
- Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX
- Track of published research, patents, or deployed models in a relevant technical domain
- Ability to translate ambiguous business problems into structured machine learning solutions
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for model deployment
Applied Scientist Jobs in Texas: Frequently Asked Questions
How do you become a applied scientist in Texas?
Applied scientist roles in Texas do not require a state-issued license, but employers consistently expect a graduate degree in computer science, statistics, applied mathematics, or a closely related field. Most Texas hiring managers look for a master's degree at minimum, with a PhD preferred for research-heavy positions. Candidates who supplement their education with published work, open-source contributions, or a demonstrable portfolio of deployed models move through the interview process faster in the Texas market.
How much do applied scientists make in Texas?
Applied scientists in Texas earn a median of about $122,090 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $64,540 for the lowest 10% to over $170,780 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire applied scientists in Texas?
Employers hiring applied scientists in Texas right now include Amazon Web Services, SentiLink, and Apple, based on current listings on Migrate Mate as of August 2026. Texas's concentration of technology campuses, energy majors, and healthcare systems means demand comes from a broader range of industries than most states, so openings appear across sectors well beyond pure software.
Which Texas cities have the most applied scientist jobs?
Austin, Texas, and Frisco have the most applied scientist openings in Texas. Austin's dense technology corridor draws the largest share, driven by major cloud and consumer-tech campuses, while Dallas benefits from a strong financial services and telecom presence, and Houston's energy and medical industries generate consistent demand for applied scientists working on optimization, forecasting, and clinical analytics.
Are there remote applied scientist jobs in Texas?
Yes, and more than most fields. Applied scientist work is largely analytical and code-based, which makes it well-suited to remote arrangements. About 100% of applied scientist openings tied to Texas are remote or hybrid as of August 2026, reflecting how broadly distributed technical teams have become. Roles focused on modeling, experimentation, and research tend to be the most remote-eligible, while positions requiring close collaboration with hardware or on-site data infrastructure are more likely to require in-person presence.
How can I get hired as a applied scientist in Texas with little or no experience?
The most realistic entry path is a research internship or rotational program at a large Texas employer while completing a graduate degree. Companies like Amazon and Meta run structured intern-to-full-time pipelines out of their Austin and Dallas offices, and several Houston-area energy firms sponsor early-career data science rotations that feed into applied scientist tracks. Candidates without prior industry experience benefit most from a strong thesis project, a Kaggle portfolio with reproducible code, or a published paper, combined with adjacent roles like data analyst or ML engineer that build production credibility before a lateral move.
Where can I find and apply to applied scientist jobs in Texas?
You can find and apply to applied scientist jobs in Texas on Migrate Mate, which lists current Texas openings. Search the available roles, find the ones that fit your background and target location, and apply directly to each position from the listing.
See All 10 Applied Scientist Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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