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Entry Level Remote Machine Learning Jobs in Alex, OK

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Entry Level Remote Machine Learning information

See Alex, OK salary details

$9

$14

$17

How much do entry level remote machine learning jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for entry level remote machine learning in Alex, OK is $14.03, according to ZipRecruiter salary data. Most workers in this role earn between $12.55 and $15.24 per hour, depending on experience, location, and employer.

How to get into entry level remote machine learning with no experience?

To start an entry-level remote machine learning role with no experience, focus on building foundational skills in programming languages like Python, learn key concepts such as data preprocessing and model training, and complete online courses or certifications in machine learning. Gaining practical experience through personal projects, participating in competitions, and creating a portfolio can also improve your chances of landing an entry-level position.

What is the difference between Entry Level Remote Machine Learning vs Entry Level Remote Data Science?

AspectEntry Level Remote Machine LearningEntry Level Remote Data Science
Required CredentialsBachelor's in CS, Math, or related; familiarity with ML frameworksBachelor's in CS, Statistics, or related; knowledge of data analysis tools
Work EnvironmentRemote, collaborative teams, coding-focusedRemote, data analysis, reporting, and visualization tasks
Industry UsageTech, AI startups, research institutionsFinance, healthcare, marketing, tech
Common Search/ComparisonYesYes

Entry Level Remote Machine Learning roles focus on developing algorithms and models using programming skills, while Entry Level Remote Data Science positions emphasize analyzing data, creating reports, and deriving insights. Both roles often require similar educational backgrounds and are common in tech-driven industries, but they differ in daily tasks and focus areas.

What job categories do people searching Entry Level Remote Machine Learning jobs in Alex, OK look for?

The top searched job categories for Entry Level Remote Machine Learning jobs in Alex, OK are:

Infographic showing various Entry Level Remote Machine Learning job openings in Alex, OK as of August 2026, with employment types broken down into 6% Internship, 63% Full Time, 19% Part Time, and 12% Contract. Highlights an 100% Remote job distribution, with an average salary of $29,181 per year, or $14 per hour.

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Oklahoma City, OK • Remote

$50 - $90/hr

Part-time

This job post has expired 1 day ago. 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.