Applied AI Engineer Jobs in Texas
Applied AI Engineer jobs in Texas are among the most active in the country, concentrated in enterprise software, defense technology, energy, and financial services, with openings at every level from entry-level ML engineer to senior principal. Austin, Dallas, and Houston anchor most of the hiring, with employers like Dell Technologies, AT&T, and ExxonMobil maintaining deep and lasting AI engineering practices in the state. The most in-demand specialties are large language model deployment, computer vision systems, and MLOps infrastructure. Find a role that fits below and apply directly.
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INTRODUCTION
Apple’s Platform Architecture group develops the next generation of Apple hardware, and the tools to make it possible. Our team builds high-performance verification systems that accelerate the development of Apple silicon. We aim to push the boundaries of pre-silicon validation with simulation solutions that apply and extend principles from hardware emulation.
We are seeking an engineer to develop and deploy agentic AI workflows that automate and optimize pre-silicon validation processes. In this role, you will bridge the gap between applied artificial intelligence and Electronic Design Automation (EDA), building autonomous agents that triage errors, tune simulation parameters, and drastically reduce maintenance burdens for silicon verification teams.
DESCRIPTION
In this role, you will focus on AI based automations, infrastructure development, and continuous experimentation at the intersection of hardware design and verification.
Responsibilities
- Design and deploy autonomous AI agents to review design changes, resolve conflicts, and triage elaboration and simulation errors.
- Develop AI-driven workflows to flag simulation performance and design concerns, automatically tune design parameters, and explore optimization candidates autonomously.
- Apply internal and external EDA tools (e.g., Logic Equivalence Checking, wave dumps, design libraries) to automatically diagnose issues and explore design alternatives.
- Build and maintain AI harnesses, scripts, and infrastructure to support continuous research and experimentation.
- Conduct data-driven experimentation to optimize prompts and harnesses; measure and improve token efficiency, task completion, and hallucination rates.
- Track and evaluate emerging machine learning and Large Language Model (LLM) use cases in the broader industry for application in silicon design workflows.
- Occasionally travel (approximately once a year) to collaborate with development groups in the US.
MINIMUM QUALIFICATIONS
- Bachelor’s degree in Computer Science, Electrical Engineering, Machine Learning, or a related field (or equivalent practical experience).
- Experience in one of the following two areas: Applied AI (experience building, deploying, and maintaining LLM-based applications, agentic workflows, or advanced prompt engineering, combined with an entry-level familiarity with EDA tools or hardware verification concepts), or EDA/Silicon (experience with RTL design, simulation, or hardware emulation platforms, combined with a demonstrated track record of working in research-oriented roles applying software automation or ML to hardware problems).
- Experience with scripting, infrastructure development, and software engineering (e.g., Python, C/C++).
PREFERRED QUALIFICATIONS
- Master’s in Computer Science, Electrical Engineering, or a related AI/Hardware field.
- Hands-on experience with Design Verification tasks requiring application of EDA tools, including Logic Equivalence Checking (LEC), linting / static analysis tools, waveform debugging, and simulation / emulation flows.
- Familiarity with Verilog, SystemVerilog, or architecting HDL testbenches for functional verification.
- Experience developing software tools for co-simulating designs across multiple high-performance platforms.
- Comfortable exploring unfamiliar codebases, researching cutting-edge techniques, and rapidly prototyping automated solutions.
- Experience applying research methods: literature review, data-driven experimentation, analyzing results.
- Strong communication skills, with the ability to collaborate effectively with cross-functional silicon engineering, design verification, and EDA development teams.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $126,800 and $220,900, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See All 17 Applied AI Engineer Jobs in Texas
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Find Applied AI Engineer JobsApplied AI Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Applied AI Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
- Apple6

- Applied Materials2

- SentiLink2

- Citi1

- GEICO1

Top Industries Hiring
- Electronics & Hardware8
- Technology & Software6
- Banking & Financial Services3
- Artificial Intelligence1
- Construction & Real Estate1
What Texas Employers Look For
The qualifications that appear most often in applied AI engineer jobs across Texas.
- Bachelor's or master's degree in computer science, machine learning, or a related engineering field
- Hands-on experience building and deploying production ML or deep learning models
- Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience with cloud platforms including AWS, Azure, or Google Cloud for model deployment
- Familiarity with MLOps tooling, CI/CD pipelines, and model monitoring in production environments
- Strong communication skills for translating AI outputs into actionable insights for business stakeholders
Applied AI Engineer Jobs in Texas: Frequently Asked Questions
How do you become a applied ai engineer in Texas?
Applied AI engineering in Texas requires no state-issued license, so the path runs through education and demonstrated technical skill. Most Texas employers expect at least a bachelor's degree in computer science, data science, or a closely related field, with a master's degree preferred at mid-level and above. Building a portfolio of deployed models, contributing to open-source projects, and earning cloud certifications from AWS or Google Cloud are the credentials that move Texas applications forward.
How much do applied AI engineers make in Texas?
Applied AI 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 applied ai engineers in Texas?
Employers hiring applied ai engineers in Texas right now include Apple, Applied Materials, and SentiLink, based on current listings on Migrate Mate as of June 2026. Texas's mix of Fortune 500 headquarters, defense contractors, and fast-growing technology firms creates a broad and consistent pipeline of applied AI roles across sectors.
Which Texas cities have the most applied ai engineer jobs?
Austin, Arlington, and Frisco lead Texas for applied ai engineer openings. Austin's dense concentration of technology company headquarters and research offices drives the highest volume, while Dallas benefits from its large financial services and telecommunications employers, and Houston's energy sector and medical center institutions generate steady demand for applied AI talent.
Are there remote applied ai engineer jobs in Texas?
Yes, and more than most fields. About 29% of applied ai engineer openings tied to Texas are remote or hybrid as of June 2026, reflecting how much of this work centers on code, model training, and analysis rather than on-site equipment. Research, experimentation, and MLOps pipeline work are the areas most commonly offered as fully remote.
How can I get hired as a applied ai engineer in Texas with little or no experience?
The most realistic entry path is through a junior ML engineer or data engineer role at a Texas technology company or large enterprise. Employers like Dell Technologies, USAA, and Texas-based defense contractors run early-career associate programs and rotational technology tracks that accept candidates with strong academic projects in lieu of industry experience. A GitHub portfolio showing end-to-end model work, even on public datasets, and an AWS or Google Cloud associate certification consistently separate new applicants in Texas hiring pipelines.
Where can I find and apply to applied ai engineer jobs in Texas?
You can find and apply to applied ai engineer jobs in Texas on Migrate Mate, which lists current Texas openings across industries and experience levels. Find a role that fits and apply directly from the listing.
See All 17 Applied AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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