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Entry Level Deep Learning Jobs in Texas (NOW HIRING)

Life Cycle Power

IT Technician- Entry Level

Houston, TX · On-site

If you enjoy helping people, solving complex IT problems, learning new trade skills, and being part ... Deep understanding of support in critical infrastructures, i.e., IT/OT environments and First ...

Motion Recruitment

Recruiter - Entry Level

Dallas, TX · On-site

$50K/yr

... deep expertise of a dedicated local market team beside you. • Facilitate positive process ... your learning throughout your time at Motion Recruitment • Ongoing one-on-one support and ...

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All JobsDeep Learning JobsEntry Level Deep Learning JobsEntry Level Deep Learning Jobs in Texas

Entry Level Deep Learning information

See Texas salary details

$18K

$78.4K

$172.8K

How much do entry level deep learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for entry level deep learning in Texas is $78,420.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,418.00 and $130,595.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Deep Learning vs Entry Level Machine Learning?

AspectEntry Level Deep LearningEntry Level Machine Learning
Required CredentialsBachelor's in CS, Data Science, or related; familiarity with neural networksBachelor's in CS, Data Science, or related; basic understanding of algorithms
Work EnvironmentResearch labs, tech companies, AI startupsTech firms, finance, healthcare, and various industries
Employer & Industry UsageAI-focused roles, research institutionsBroader industry applications, including analytics and automation
Common Search & ComparisonOften compared for specialization in neural networks and deep architecturesMore general, covers broader ML techniques

Entry Level Deep Learning focuses on neural networks and complex models, often requiring knowledge of frameworks like TensorFlow or PyTorch. Entry Level Machine Learning covers a wider range of algorithms and techniques. Both roles share foundational skills but differ in specialization and application scope.

What engineer makes $500,000 a year?

Highly experienced engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially in senior or executive roles at large tech companies. These roles often require advanced skills, extensive experience, and sometimes stock options or bonuses as part of compensation packages.

Can I get an AI job with no experience?

Entry level deep learning positions often require some foundational knowledge of programming, machine learning concepts, and tools like Python and TensorFlow. While prior experience is helpful, candidates can improve their chances by completing relevant online courses, building projects, and gaining certifications to demonstrate their skills to employers.

What are entry level deep learning jobs?

Entry level deep learning jobs are positions designed for individuals who are new to the field of artificial intelligence and machine learning, typically recent graduates or those with limited professional experience. These roles often involve assisting in building, training, and testing neural network models, as well as preprocessing data and supporting senior data scientists or machine learning engineers. Entry level positions may also include tasks such as researching recent advancements, implementing standard algorithms, and contributing to team projects under supervision. A strong foundation in Python, deep learning frameworks like TensorFlow or PyTorch, and an understanding of basic machine learning concepts are usually required.

Which 3 jobs will survive AI?

Entry Level Deep Learning roles are likely to persist in fields requiring complex problem-solving, creativity, and domain expertise, such as AI research, data science, and machine learning engineering. These jobs involve tasks that are difficult to automate fully and often require specialized skills, programming knowledge, and continuous learning to adapt to evolving technologies.

What are some common challenges faced by entry-level deep learning professionals, and how can they be addressed?

Entry-level deep learning professionals often encounter challenges such as understanding complex architectures, managing large datasets, and optimizing model performance. Navigating unfamiliar frameworks and debugging code can also be daunting at first. These challenges can be addressed by seeking mentorship from experienced colleagues, participating in code reviews, and dedicating time to hands-on projects. Additionally, staying updated with the latest research and utilizing online communities or forums can provide valuable support and resources.

What are the key skills and qualifications needed to thrive as an Entry Level Deep Learning professional, and why are they important?

To thrive as an Entry Level Deep Learning professional, you need a solid understanding of machine learning fundamentals, mathematics (especially linear algebra and calculus), and proficiency in programming languages such as Python. Experience with frameworks like TensorFlow or PyTorch and familiarity with version control systems like Git are typically required. Strong problem-solving abilities, eagerness to learn, and the ability to work collaboratively set candidates apart in this field. These skills and qualities are essential for building, troubleshooting, and improving deep learning models in a rapidly evolving technical landscape.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and programming. These positions usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Entry-level roles in deep learning generally do not reach this salary level, which is reserved for experienced professionals with significant expertise and responsibilities.
What are the most commonly searched types of Deep Learning jobs in Texas? The most popular types of Deep Learning jobs in Texas are:
What are popular job titles related to Entry Level Deep Learning jobs in Texas? For Entry Level Deep Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Entry Level Deep Learning jobs in Texas look for? The top searched job categories for Entry Level Deep Learning jobs in Texas are:
Entry Level Deep Learning jobs near you
Infographic showing various Entry Level Deep Learning job openings in Texas as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $78,420 per year, or $37.7 per hour.
ASIC Design Verification Engineer - New College Grad 2026

ASIC Design Verification Engineer - New College Grad 2026

Nvidia Corporation

Austin, TX • On-site

$134K - $164K/yr

Full-time

Re-posted 21 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a "learning machine" that constantly evolves by adapting to new opportunities which are hard to solve, that only we can pursue, and that matter to the world. This is our life's work, to amplify human inventiveness and intelligence.
The NVIDIA System-On-Chip (SOC) group is looking for an entry level ASIC Verification Engineer! In this position you will have the chance to create a high-level and broad impact at NVIDIA working on a system-level IP responsible for measuring performance on multiple projects. Your focus will be on verifying and improving the related verification methodologies for the corresponding design (RTL). For this position, you should have real passion for verification methodologies and implementation that enable high quality system-level IP design and robust verification at multiple environment levels (e.g., unit, sub-system, and SOC).
What you'll be doing:
  • Design and maintain the unit level/sub-system Verification environment.
  • Understand the architecture specifications, develop and carry out the test plan to verify the design.
  • Create the UVM components, sequences, tests and scoreboards.
  • Sign off on the verification efforts with very high quality code and functional coverage.
  • Launch regressions, resolve the issues, and make forward progress towards achieving the DV milestone targets
  • Automate the manual steps involved in launching build, regression, and triages.
  • Collaborate with architects, designers, and software engineers to achieve the project goals.
  • Pro-actively contribute to improving the efficiency of the testbenches by embracing the latest techniques.

What we need to see:
  • Completing an MS or higher in Computer or Electrical Engineering (or equivalent experience).
  • Experience in System Verilog, UVM and in general OOPS based programming.
  • Strong coding skills in Python or other industry-standard scripting languages.
  • Strong understanding of RTL design (Verilog).
  • Good understanding of computer architecture fundamentals.
  • Familiarity with verification tools such as VCS or equivalent simulation tools, and debug tools like Verdi.

With industry-leading salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. The most forward-thinking engineers in the world do their life's work at NVIDIA. If you're creative and autonomous, with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until January 13, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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