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Learning Ai Jobs in Texas (NOW HIRING)

webAI

Director of Applied AI

Austin, TX · On-site

Every leader in this company is hands-on. • 8+ years of experience in applied machine learning, AI engineering, or related fields, with at least 3 years in a leadership role. • Proven track ...

Northern Base

Senior AI ML Engineer

Irving, TX · On-site

$100K - $137K/yr

... Learning Engineering, Production ML Deployment, and end-to-end AI solution development ✔ Experience building LLM-powered RAG (Retrieval-Augmented Generation) and Agentic AI systems ✔ Strong ...

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webAI Inc

Director of Applied AI

Austin, TX · On-site

Strong expertise with LLMs, generative AI, machine learning workflows. * Hands-on experience building or integrating AI systems for customer-facing applications. * Proficiency in Python and modern ML ...

IT America Inc

Agentic AI Engineer Lead

Dallas, TX · On-site

$101K - $133K/yr

The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be ...

Cloudera

Staff Software Engineer - AI

Austin, TX · Hybrid

You will be responsible for helping design, build, and deliver a platform that not only accelerates machine learning & AI from exploration to production but also enables enterprises to create ...

Cloudera

Staff Software Engineer - AI

Austin, TX · Hybrid

You will be responsible for helping design, build, and deliver a platform that not only accelerates machine learning & AI from exploration to production but also enables enterprises to create ...

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning ...

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All JobsLearning Ai JobsLearning Ai Jobs in Texas

Learning Ai information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, machine learning executive, or senior data scientist, often requiring advanced skills, extensive experience, and sometimes equity or bonuses. These roles are usually found in large tech companies or startups with significant AI investments and may involve leadership, strategic planning, and cutting-edge development.

What is a Learning AI?

A Learning AI, or Artificial Intelligence that learns, refers to computer systems that can improve their performance over time by analyzing data and experiences. These systems use techniques such as machine learning and deep learning to adapt to new information, recognize patterns, and make predictions or decisions without being explicitly programmed for every task. Learning AI is used in many applications, including recommendation engines, language translation, and autonomous vehicles. As technology advances, Learning AI continues to play a crucial role in automating complex tasks and enhancing decision-making processes.

What jobs can I get if I learn AI?

Learning AI can qualify you for roles such as AI engineer, machine learning engineer, data scientist, or AI researcher. These positions typically require skills in programming, data analysis, and familiarity with AI frameworks like TensorFlow or PyTorch, and often involve developing algorithms, models, and applications across various industries.

What is the difference between Learning Ai vs Data Scientist?

AspectLearning AiData Scientist
Required CredentialsTypically a degree in Computer Science, AI, or related fields; certifications in AI/MLDegree in Computer Science, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness environments, analyzing data to inform decisions across industries
Employer & Industry UsagePrimarily in AI development, research, and product creationAcross finance, healthcare, marketing, and other sectors for data analysis

Learning Ai focuses on developing algorithms and models that enable machines to learn and improve autonomously, often involving deep learning and neural networks. Data Scientists analyze and interpret complex data to help organizations make informed decisions. While both roles require knowledge of machine learning, Learning Ai is more centered on creating AI systems, whereas Data Scientists focus on extracting insights from data.

Can I get paid to learn AI?

Learning AI can be financially supported through internships, apprenticeships, or training programs that offer stipends or salaries. Some companies and educational platforms also provide paid opportunities for gaining skills in AI, machine learning, and data science while working on real projects. However, most formal learning paths require self-investment or sponsorship until you acquire marketable skills for paid roles.

How do Learning AI professionals typically collaborate with subject matter experts to develop effective training solutions?

Learning AI professionals frequently work alongside subject matter experts (SMEs) to ensure that AI-driven training tools and content are accurate, relevant, and engaging. This collaboration often involves regular meetings to gather domain-specific knowledge, iterative review of training modules, and feedback sessions to fine-tune AI models for optimal learning outcomes. Clear communication and a strong partnership with SMEs are essential, as they help bridge technical AI capabilities with real-world educational needs, resulting in more impactful and user-friendly learning solutions.

How can I start a career in AI?

To start a career in AI, develop a strong foundation in mathematics, programming (especially Python), and machine learning concepts. Gaining experience through online courses, certifications, and projects using tools like TensorFlow or PyTorch can help build practical skills and improve employability in the field.

What are the key skills and qualifications needed to thrive as a Learning AI Engineer, and why are they important?

To thrive as a Learning AI Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree or certification. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud computing platforms is typically required. Strong problem-solving skills, adaptability, and effective communication set outstanding professionals apart in this field. These skills are crucial for building, deploying, and refining AI models that solve real-world problems efficiently and ethically.
What are popular job titles related to Learning Ai jobs in Texas? For Learning Ai jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Learning Ai jobs in Texas look for? The top searched job categories for Learning Ai jobs in Texas are:
What cities in Texas are hiring for Learning Ai jobs? Cities in Texas with the most Learning Ai job openings:
Learning Ai jobs near you
Infographic showing various Learning Ai job openings in Texas as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution.

Machine Learning & AI Infrastructure Engineer

KORE1 Technologies

Houston, TX • Remote

$190K/yr

Contractor

Re-posted 26 days ago

Job description


KORE1, a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Machine Learning & AI Infrastructure Engineer that is fully remote. 

Summary:
We are seeking a Machine Learning & AI Infrastructure Engineer to help design, deploy, and support advanced AI, machine learning, and high-performance computing (HPC) environments. This hands-on technical role will work directly with compute, storage, networking, and containerized infrastructure to deliver scalable, high-performance solutions for enterprise, healthcare, research, and academic organizations.
The ideal candidate is passionate about AI infrastructure, thrives in complex technical environments, and enjoys solving challenging engineering problems while working alongside cross-functional teams.
Key Responsibilities
  • Deploy, administer, and optimize AI and HPC infrastructure environments.
  • Support compute, storage, networking, and container platforms across customer and internal environments.
  • Troubleshoot system performance, reliability, and scalability issues.
  • Assist with infrastructure automation and operational improvements.
  • Collaborate with engineering teams to design and implement modern AI and machine learning platforms.
  • Monitor and maintain infrastructure to ensure high availability and performance.
  • Support customer implementations and ongoing operational needs.

Required Qualifications
  • Strong experience administering HPC bare-metal environments.
  • Experience with NVIDIA Base Command Manager, Bright Cluster Manager, or similar HPC management platforms preferred.
  • Hands-on Kubernetes administration experience, particularly with persistent storage provisioning and CSI integrations.
  • Strong Linux administration skills, preferably Ubuntu.
  • Experience with Bash and/or Python scripting.
  • Strong troubleshooting and systems engineering capabilities.

Preferred Qualifications
  • Experience administering enterprise storage platforms such as Dell PowerScale/Isilon, VAST Storage, NetApp ONTAP, DDN IntelliFlash, or similar technologies.
  • Experience with DDN Exascaler, Lustre, or other parallel file systems.
  • Containerization and container orchestration experience.
  • Familiarity with InfiniBand networking and NVIDIA UFM.
  • Experience supporting enterprise Ethernet networking environments.
  • Exposure to AI, machine learning, or GPU-accelerated computing environments.

What Success Looks Like
  • Reliable deployment and operation of AI and HPC environments.
  • Strong system performance, scalability, and uptime.
  • Effective collaboration with engineering and customer teams.
  • Continuous improvement of infrastructure automation and operational processes.
  • Successful delivery of complex technical solutions supporting advanced AI and research initiatives.




Compensation depends on experience but is typically $170-190k/year.

ABOUT KORE1
Specializing in professional and technical recruiting, KORE1 is committed to supporting top IT, Engineering, Creative, Scientific, Accounting and Finance professionals in their career paths. We build deep relationships with leading companies, connecting them to exceptional talent every day. With extensive industry expertise and unmatched opportunities, our goal is to provide a unique experience for our contractors and consultants as they prepare for their next role. We are passionate about matching the right people with the right companies.

Kore1 provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Kore1 complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Kore1 expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of Kore1's employees to perform their job duties may result in discipline up to and including discharge.
Education:Employment Type: CONTRACTOR

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