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Remote Machine Learning Ops Engineer Jobs in Austin, TX

AI Engineer

Austin, TX · On-site +1

$140K - $200K/yr

Remote (United States) Compensation: $140,000 - $200,000 base Visa Sponsorship: None available ... About the Role As an AI Engineer, you will design, train, and deploy machine learning models and ...

As a part of our team, you will leverage your analytical skills and expertise in machine learning ... As part of a global team of developers and analysts, the Data Scientist will work with a larger ...

Create predictive models and machine-learning algorithms * Modify and combine different models ... Work together with engineering and product development teams Data Scientist requirements are: * 3+ ...

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

... machine learning engineers, research engineers, AI researchers, domain experts, and other ... Ability to work independently in a remote, fast-paced environment. Other Traits * Naturally curious ...

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Showing results 1-20

Remote Machine Learning Ops Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

How much do remote machine learning ops engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for remote machine learning ops engineer in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 per year, depending on experience, location, and employer.
What cities near Austin, TX are hiring for Remote Machine Learning Ops Engineer jobs? Cities near Austin, TX with the most Remote Machine Learning Ops Engineer job openings:
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Austin, TX • Remote

$50 - $90/hr

Part-time

Posted 12 days ago


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.