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Remote Llm Researcher Jobs (NOW HIRING)

Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks ... Familiarity with current LLM architectures, prompt engineering techniques, and security assessment ...

Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks ... Familiarity with current LLM architectures, prompt engineering techniques, and security assessment ...

Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks ... Familiarity with current LLM architectures, prompt engineering techniques, and security assessment ...

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Remote Llm Researcher information

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$30K

$113.1K

$164.5K

How much do remote llm researcher jobs pay per year?

As of Jul 5, 2026, the average yearly pay for remote llm researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote LLM Researcher, and why are they important?

To thrive as a Remote LLM Researcher, you need a strong background in machine learning, natural language processing, and deep learning, typically supported by an advanced degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience working with large language models (LLMs), and knowledge of distributed computing tools are commonly required. Outstanding problem-solving abilities, communication skills, and the ability to work independently are essential soft skills for remote collaboration and research innovation. These skills enable effective development, evaluation, and deployment of advanced language models in a distributed team environment.

How do Remote LLM Researchers typically collaborate with cross-functional teams given their distributed work environment?

Remote LLM Researchers often work closely with data scientists, machine learning engineers, and product managers via virtual collaboration tools such as Slack, Zoom, and GitHub. Regular meetings, shared documentation, and project management platforms help maintain clear communication and alignment on research goals. Being proactive in sharing updates, seeking feedback, and participating in code reviews is essential for seamless teamwork. This collaborative approach ensures research findings can be effectively integrated into products and services, despite the physical distance.

What is the difference between Remote Llm Researcher vs Remote Data Scientist?

AspectRemote Llm ResearcherRemote Data Scientist
CredentialsAdvanced degrees in AI, NLP, or related fields; research experienceDegree in Data Science, Statistics, or Computer Science; often includes certifications
Work EnvironmentResearch-focused, often in AI labs or tech companies, remote options availableData analysis, modeling, and visualization tasks, remote or on-site
Industry UsageAI research, NLP development, machine learning innovationBusiness analytics, predictive modeling, data-driven decision making

Remote Llm Researchers focus on developing and improving large language models through research and experimentation, often in AI labs. Remote Data Scientists analyze data to generate insights and build predictive models. While both roles require strong technical skills, Remote Llm Researchers are more research-oriented, whereas Remote Data Scientists focus on applying data techniques to solve business problems.

What is a Remote LLM Researcher?

A Remote LLM Researcher is a professional who studies and develops large language models (LLMs), such as GPT or BERT, while working from a location outside of a traditional office setting. Their work typically involves conducting experiments, analyzing data, improving model architectures, and publishing findings in the field of natural language processing (NLP). Remote LLM Researchers often collaborate with colleagues online, use cloud-based computing resources, and contribute to advancements in AI language technologies. This role requires strong programming skills, a background in machine learning, and the ability to work independently in a distributed team environment.
More about Remote Llm Researcher jobs
What cities are hiring for Remote Llm Researcher jobs? Cities with the most Remote Llm Researcher job openings:
What are the most commonly searched types of Llm Researcher jobs? The most popular types of Llm Researcher jobs are:
What states have the most Remote Llm Researcher jobs? States with the most job openings for Remote Llm Researcher jobs include:
Infographic showing various Remote Llm Researcher job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Mesa, AZ โ€ข Remote

$50 - $90/hr

Part-time

Posted 5 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 โ€” 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 communityโ€”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.