AI ML Intern Jobs in Texas
AI ML Intern jobs in Texas are among the most actively recruited entry-level technology positions in the country, concentrated in software, semiconductor, aerospace, and energy tech sectors with demand from first-year students through advanced graduate candidates. Austin, Dallas, and Houston anchor most of the hiring, with major employers like Texas Instruments, Dell Technologies, and Lockheed Martin running structured internship programs. The most sought-after specialties are natural language processing, computer vision, and ML infrastructure engineering. Find a role that fits below and apply directly.
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DESCRIPTION
We are seeking a Cloud Hardware Development Engineer to define server architectures based on workload demand, translate them into detailed component specifications, and drive validation from PCBA bring-up through rack integration. You will lead ODM design partners through development and production, triage hardware issues across manufacturing and datacenters, and own fleet quality metrics post-launch.
What You Will Do
You will define the hardware that runs the world's largest AI training workloads. Your designs span thermal, mechanical, power, and signal integrity across GPU-accelerated platforms. You will drive validation from first silicon through fleet-scale deployment, triage failures correlating across PCIe, power delivery, memory, and accelerator interconnects, and feed root cause findings back into design improvements. When a new server platform launches at a large scale, the architecture, component choices, and quality gates are yours.
Key job responsibilities
Architecture & Design
- Define server architectures based on workload demand and customer requirements, translating them into detailed designs and component specifications that enable high-performance AI training and inference at scale
- Work with interdisciplinary teams of component, firmware, test, qualification, and integration engineers to deliver cohesive designs
- Drive design reviews with ODM/JDM partners covering schematic, layout, BOM, and manufacturing DFx (Design for Test, Design for Manufacturing)
Validation & Bring-up
- Define and execute validation strategies from PCBA bring-up through server and rack integration — covering power sequencing, signal integrity, thermal characterization, and accelerator interconnect performance
- Own hardware debug during EVT/DVT/PVT builds, correlating failures across PCIe, power rails, memory channels, and GPU subsystems
- Triage hardware issues at both ODM facilities and datacenters, conduct root cause analysis, and implement corrective actions
Fleet Quality & Continuous Improvement
- Own fleet quality metrics post-launch: server-level annualized failure rates and component-level failure modes
- Monitor operational telemetry to identify systemic issues and drive design or process changes for current and future platforms
- Partner with test and automation teams to improve manufacturing yield and reduce test dwell times
Cross-Team Collaboration
- Work with EC2 architecture teams to align on instance definitions, workload requirements, and platform trade-offs
- Drive ODM/JDM design partners through development milestones and production ramp
- Collaborate with firmware, software, and operations teams to ensure designs are debuggable, serviceable, and automation-ready
May require occasional (
The Ideal Candidate
You think across the full hardware stack — from silicon packaging and power delivery to rack-level thermal and mechanical design. You are as comfortable reviewing a schematic as you are analyzing fleet failure data. You drive quality through data, not assumption, and you hold design partners to the same standard you hold yourself. You mentor and develop junior engineers, contribute to hiring, and share your expertise to make the team stronger.
Why You Will Love It
The world's most advanced frontier models train on the hardware you design. You will see your architecture decisions scale to a large fleet of servers. The team is deeply technical and high-trust — you own platforms end to end from architecture definition through fleet operations.
A day in the life
You start the day reviewing thermal and power validation data from an EVT build at your ODM partner. Mid-morning, you join a design review to close signal integrity findings on a high-speed accelerator interconnect. In the afternoon, you triage a fleet quality signal — correlating component-level failure data with manufacturing lot information to identify a systemic issue. You end the day aligning with architecture teams on requirements for the next-generation platform.
About the team
The Hardware Engineering AI/ML UltraServer platform team is a group of engineers and technical program managers directly responsible for launching GPU-accelerated servers into the AWS fleet. Located in Seattle, Austin, and Cupertino, we collaborate with global development teams and ODM partners to deliver next-generation AI/ML infrastructure deployed in datacenters worldwide. We move fast with small, empowered teams delivering end-to-end — from server conception through fleet-scale operations.
BASIC QUALIFICATIONS
- Bachelor's degree in electrical engineering, computer engineering, or equivalent
- Experience in developing functional specifications, design verification plans and functional test procedures
- 7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms
- Experience in one or more server technologies: thermal/mechanical design, power delivery, high-speed signal integrity, or accelerator subsystems
- Experience leading hardware development through full product lifecycle (concept through production ramp)
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Electrical Engineering, Computer Engineering, or a related field
- 5+ years of experience working with ODMs through the product development and manufacturing lifecycle (EVT, DVT, PVT)
- In-depth expertise in high-speed bus design, signal integrity analysis, or power delivery for GPU/accelerator platforms
- 5+ years of experience with hardware bring-up, debug, and root cause analysis across PCIe, NVMe, memory, and accelerator interconnects
- Experience owning fleet quality metrics and driving design improvements based on operational failure data
- Experience with thermal/mechanical design for high-power-density compute platforms (liquid cooling, air cooling, or hybrid)
- Experience working in large-scale datacenter or cloud environments
- Track record of defining engineering standards and design best practices adopted across teams or partner organizations
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, Cupertino - 183,000.00 - 247,600.00 USD annually
USA, TX, Austin - 159,200.00 - 215,300.00 USD annually
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually
DESCRIPTION
We are seeking a Cloud Hardware Development Engineer to define server architectures based on workload demand, translate them into detailed component specifications, and drive validation from PCBA bring-up through rack integration. You will lead ODM design partners through development and production, triage hardware issues across manufacturing and datacenters, and own fleet quality metrics post-launch.
What You Will Do
You will define the hardware that runs the world's largest AI training workloads. Your designs span thermal, mechanical, power, and signal integrity across GPU-accelerated platforms. You will drive validation from first silicon through fleet-scale deployment, triage failures correlating across PCIe, power delivery, memory, and accelerator interconnects, and feed root cause findings back into design improvements. When a new server platform launches at a large scale, the architecture, component choices, and quality gates are yours.
Key job responsibilities
Architecture & Design
- Define server architectures based on workload demand and customer requirements, translating them into detailed designs and component specifications that enable high-performance AI training and inference at scale
- Work with interdisciplinary teams of component, firmware, test, qualification, and integration engineers to deliver cohesive designs
- Drive design reviews with ODM/JDM partners covering schematic, layout, BOM, and manufacturing DFx (Design for Test, Design for Manufacturing)
Validation & Bring-up
- Define and execute validation strategies from PCBA bring-up through server and rack integration — covering power sequencing, signal integrity, thermal characterization, and accelerator interconnect performance
- Own hardware debug during EVT/DVT/PVT builds, correlating failures across PCIe, power rails, memory channels, and GPU subsystems
- Triage hardware issues at both ODM facilities and datacenters, conduct root cause analysis, and implement corrective actions
Fleet Quality & Continuous Improvement
- Own fleet quality metrics post-launch: server-level annualized failure rates and component-level failure modes
- Monitor operational telemetry to identify systemic issues and drive design or process changes for current and future platforms
- Partner with test and automation teams to improve manufacturing yield and reduce test dwell times
Cross-Team Collaboration
- Work with EC2 architecture teams to align on instance definitions, workload requirements, and platform trade-offs
- Drive ODM/JDM design partners through development milestones and production ramp
- Collaborate with firmware, software, and operations teams to ensure designs are debuggable, serviceable, and automation-ready
May require occasional (
The Ideal Candidate
You think across the full hardware stack — from silicon packaging and power delivery to rack-level thermal and mechanical design. You are as comfortable reviewing a schematic as you are analyzing fleet failure data. You drive quality through data, not assumption, and you hold design partners to the same standard you hold yourself. You mentor and develop junior engineers, contribute to hiring, and share your expertise to make the team stronger.
Why You Will Love It
The world's most advanced frontier models train on the hardware you design. You will see your architecture decisions scale to a large fleet of servers. The team is deeply technical and high-trust — you own platforms end to end from architecture definition through fleet operations.
A day in the life
You start the day reviewing thermal and power validation data from an EVT build at your ODM partner. Mid-morning, you join a design review to close signal integrity findings on a high-speed accelerator interconnect. In the afternoon, you triage a fleet quality signal — correlating component-level failure data with manufacturing lot information to identify a systemic issue. You end the day aligning with architecture teams on requirements for the next-generation platform.
About the team
The Hardware Engineering AI/ML UltraServer platform team is a group of engineers and technical program managers directly responsible for launching GPU-accelerated servers into the AWS fleet. Located in Seattle, Austin, and Cupertino, we collaborate with global development teams and ODM partners to deliver next-generation AI/ML infrastructure deployed in datacenters worldwide. We move fast with small, empowered teams delivering end-to-end — from server conception through fleet-scale operations.
BASIC QUALIFICATIONS
- Bachelor's degree in electrical engineering, computer engineering, or equivalent
- Experience in developing functional specifications, design verification plans and functional test procedures
- 7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms
- Experience in one or more server technologies: thermal/mechanical design, power delivery, high-speed signal integrity, or accelerator subsystems
- Experience leading hardware development through full product lifecycle (concept through production ramp)
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Electrical Engineering, Computer Engineering, or a related field
- 5+ years of experience working with ODMs through the product development and manufacturing lifecycle (EVT, DVT, PVT)
- In-depth expertise in high-speed bus design, signal integrity analysis, or power delivery for GPU/accelerator platforms
- 5+ years of experience with hardware bring-up, debug, and root cause analysis across PCIe, NVMe, memory, and accelerator interconnects
- Experience owning fleet quality metrics and driving design improvements based on operational failure data
- Experience with thermal/mechanical design for high-power-density compute platforms (liquid cooling, air cooling, or hybrid)
- Experience working in large-scale datacenter or cloud environments
- Track record of defining engineering standards and design best practices adopted across teams or partner organizations
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, Cupertino - 183,000.00 - 247,600.00 USD annually
USA, TX, Austin - 159,200.00 - 215,300.00 USD annually
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually
See All 18 AI ML Intern Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find AI ML Intern JobsAI ML Intern Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
AI ML Intern Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Retail
- Banking & Financial Services
- E-Commerce & Online Marketplaces
- Electronics & Hardware
What Texas Employers Look For
The qualifications that appear most often in AI ML intern jobs across Texas.
- Currently enrolled in a bachelor's or master's degree program in computer science, data science, or a related field
- Hands-on experience with Python and at least one ML framework such as PyTorch or TensorFlow
- Familiarity with supervised and unsupervised learning methods and model evaluation techniques
- Experience working with large datasets, data preprocessing pipelines, and feature engineering
- Exposure to cloud platforms such as AWS, Google Cloud, or Azure for model training and deployment
- Strong grasp of linear algebra, probability, and statistics as applied to machine learning problems
AI ML Intern Jobs in Texas: Frequently Asked Questions
How do you become a ai ml intern in Texas?
The most direct path is enrolling in a computer science, electrical engineering, or data science program at a Texas university and building a project portfolio before recruiting season opens. Texas has no state license or board for this role. Employers at Texas Instruments, Dell, and major Austin tech firms typically recruit through university career fairs and online applications, prioritizing candidates who can show working ML projects, GitHub repositories, or research involvement alongside their coursework.
Which companies hire ai ml interns in Texas?
Employers hiring ai ml interns in Texas right now include Amazon Web Services, AMD, and Photon, based on current listings on Migrate Mate as of September 2026. Texas's dense concentration of semiconductor, defense, and enterprise software firms means structured intern cohorts are common, and many convert high-performing interns to full-time roles after graduation.
Which Texas cities have the most ai ml intern jobs?
Austin, Irving, and Houston hold the largest share of ai ml intern openings in Texas. Austin leads because of its dense cluster of tech headquarters and startups, Dallas draws volume from enterprise software and financial technology firms based in the Metroplex, and Houston's openings are driven by energy technology companies and aerospace contractors such as those supporting NASA's Johnson Space Center.
Are there remote ai ml intern jobs in Texas?
Yes, and more than most fields, since ML work centers on code, data, and model experimentation that translates well to distributed teams. About 43% of ai ml intern openings tied to Texas are remote or hybrid as of September 2026, reflecting genuine flexibility from tech-forward employers. Roles focused on data pipeline work and model prototyping tend to be the most remote-friendly, while positions involving specialized hardware or on-site GPU clusters typically require in-person attendance.
How can I get hired as a ai ml intern in Texas with little or no experience?
The most realistic entry point is an undergraduate research assistantship at a Texas university such as UT Austin, Texas A&M, or Rice, where faculty labs actively recruit students with no prior industry background. From there, open-source contributions, Kaggle competition results, and a documented GitHub portfolio give Texas employers a concrete signal. Large Texas firms including Dell and Texas Instruments run early-identification programs that accept first- and second-year undergraduates, and adjacent roles in data labeling or QA engineering are common lateral moves that lead to ML intern offers.
Where can I find and apply to ai ml intern jobs in Texas?
You can find and apply to ai ml intern jobs in Texas on Migrate Mate, which lists current Texas openings updated in real time. Search the listings, find roles that match your skills and availability, and apply directly to each employer through the listing. No sign-up is required to search or review openings.
See All 18 AI ML Intern Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find AI ML Intern Jobs