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Remote Nvidia Machine Learning Jobs in Texas (NOW HIRING)

YO AI Labs

Senior Software Engineer - Remote

Austin, TX · Remote

$121K - $160K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

YO AI Labs

Senior Software Engineer - Remote

Texas City, TX · Remote

$104K - $138K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Blue Cross of Idaho

AI Technical Lead

Meridian, TX · On-site +1

... remote within a mutually acceptable location. #LI-Hybrid Success Looks Like: * AI systems move ... Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

Delan Associates, Inc.

AI Lead Engineer

Dallas, TX · On-site +1

$101K - $133K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills * Artificial Intelligence (AI) & Machine Learning (ML) * Deep Learning * Generative AI (GenAI) * Large Language Models (LLMs) * Prompt ...

Delan Associates, Inc

AI Lead Engineer

Dallas, TX · Remote

$101K - $133K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills Artificial Intelligence (AI) & Machine Learning (ML) Deep Learning Generative AI (GenAI) Large Language Models (LLMs) Prompt ...

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All JobsNvidia Machine Learning JobsRemote Nvidia Machine Learning JobsRemote Nvidia Machine Learning Jobs in Texas

Remote Nvidia Machine Learning information

What is the difference between Remote Nvidia Machine Learning vs Remote Data Scientist?

AspectRemote Nvidia Machine LearningRemote Data Scientist
Required CredentialsDeep learning, GPU programming, Nvidia certificationsStatistics, programming, data analysis
Work EnvironmentFocus on GPU-accelerated ML models, Nvidia toolsData analysis, modeling, visualization
Industry UsageAI, autonomous vehicles, gaming, HPCBusiness analytics, research, finance

Remote Nvidia Machine Learning specialists focus on developing GPU-accelerated AI models using Nvidia technologies, often requiring specific certifications and expertise in GPU programming. In contrast, Remote Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and programming skills, Nvidia Machine Learning roles are more specialized in GPU-based AI development, whereas Data Scientists have broader data analysis responsibilities.

What are the most commonly searched types of Nvidia Machine Learning jobs in Texas? The most popular types of Nvidia Machine Learning jobs in Texas are:
What cities in Texas are hiring for Remote Nvidia Machine Learning jobs? Cities in Texas with the most Remote Nvidia Machine Learning job openings:
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AI Safety Engineer (Red Teaming) - Remote

micro1 AI

San Antonio, TX • Remote

$50 - $90/hr

Part-time

This job post has expired today. Applications are no longer accepted.

Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert


Role Type: Contractor


Location: Remote


micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
  2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
  3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
  4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
  5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
  6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.


Preferred Qualifications

  1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
  2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
  3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
  4. High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations.
  5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
  6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
  7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.

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