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Remote Generative Ai Engineer Jobs in Colorado (NOW HIRING)

Remote micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

Remote micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

Job Title AI Deployment Engineer The AI Deployment Engineer will support CoorsTek's AI and ... Salary range subject to location, as this role can be remote** Roles and Responsibilities: * Design ...

Remote micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

Remote micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

Showing results 41-60

Remote Generative Ai Engineer information

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.
What are the most commonly searched types of Generative Ai Engineer jobs in Colorado? The most popular types of Generative Ai Engineer jobs in Colorado are:
What are popular job titles related to Remote Generative Ai Engineer jobs in Colorado? For Remote Generative Ai Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Generative Ai Engineer jobs in Colorado look for? The top searched job categories for Remote Generative Ai Engineer jobs in Colorado are:
What cities in Colorado are hiring for Remote Generative Ai Engineer jobs? Cities in Colorado with the most Remote Generative Ai Engineer job openings:
Infographic showing various Remote Generative Ai Engineer job openings in Colorado as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Denver, CO • 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.