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Remote Cyber Security Machine Learning Jobs in Portland, OR

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... PRIMARY RESPONSIBILITIES * Hands-on development and write algorithms in machine learning ...

NAVEX

Senior Product Manager, AI

Lake Oswego, OR · On-site +1

$130K/yr

Analyze data pipelines, machine learning algorithms, and automated systems. Utilize AI techniques ... Experience in leading remote or geographically dispersed AI teams * High tolerance for ambiguity ...

micro1 AI

Engineering AI Evaluator (PhD)

Portland, OR · Remote

$80 - $90/hr

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 ...

micro1 AI

Domain Expert - (STEM PhD)

Portland, OR · Remote

$80 - $90/hr

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 ...

DataAnnotation

QA Engineer - AI Trainer

Portland, OR · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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All JobsCyber Security Machine Learning JobsRemote Cyber Security Machine Learning JobsRemote Cyber Security Machine Learning Jobs in Portland, OR

Remote Cyber Security Machine Learning information

See Portland, OR salary details

$43K

$130.3K

$190.9K

How much do remote cyber security machine learning jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote cyber security machine learning in Portland, OR is $130,325.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,200.00 and $150,600.00 per year, depending on experience, location, and employer.

What is the difference between Remote Cyber Security Machine Learning vs Remote Cyber Security Analyst?

AspectRemote Cyber Security Machine LearningRemote Cyber Security Analyst
Required CredentialsCertifications in cybersecurity and machine learning (e.g., CISSP, CompTIA Security+, Python, ML certifications)Certifications in cybersecurity (e.g., CISSP, CompTIA Security+)
Work EnvironmentFocus on developing algorithms, analyzing data, and automating security processesMonitoring security alerts, investigating incidents, and implementing security measures
Employer & Industry UsageTech companies, cybersecurity firms, organizations leveraging AI for securityOrganizations across industries needing security monitoring and incident response

Remote Cyber Security Machine Learning specialists develop AI-driven security tools, while Remote Cyber Security Analysts focus on monitoring and responding to threats. Both roles require cybersecurity knowledge, but the former emphasizes data analysis and machine learning skills, whereas the latter concentrates on security operations and incident management.

What is a Remote Cyber Security Machine Learning job?

A Remote Cyber Security Machine Learning job involves using machine learning techniques to detect, prevent, and respond to cyber threats, all while working from a remote location. Professionals in this role develop and deploy algorithms that can identify patterns of malicious activity, automate threat detection, and enhance security protocols. They work with large datasets, collaborate with security teams, and continuously update models to address emerging threats. This position combines expertise in both cyber security and machine learning, making it critical for modern, data-driven security operations.

How does a Remote Cyber Security Machine Learning professional typically collaborate with cross-functional teams?

As a Remote Cyber Security Machine Learning professional, you'll often work closely with cybersecurity analysts, data engineers, and IT staff to design, implement, and refine machine learning models that detect and prevent threats. Collaboration happens primarily through virtual meetings, shared documentation, and project management tools, ensuring that everyone stays aligned despite geographic distances. Clear communication and proactivity are key, as you'll need to translate complex machine learning concepts into actionable insights for team members with varying technical backgrounds. Regular updates and feedback loops help ensure that models are robust, effective, and aligned with organizational security goals.

What are the key skills and qualifications needed to thrive as a Remote Cyber Security Machine Learning Specialist, and why are they important?

To excel in a Remote Cyber Security Machine Learning role, you need a strong background in computer science, cybersecurity principles, and machine learning algorithms, typically supported by a relevant degree and experience. Familiarity with tools like Python, TensorFlow, PyTorch, and security platforms such as SIEM systems, along with certifications like CISSP or CEH, is often required. Excellent analytical thinking, problem-solving skills, and clear remote communication set top performers apart. These abilities are crucial for proactively identifying and mitigating threats using advanced AI techniques while collaborating effectively in distributed teams.
What are popular job titles related to Remote Cyber Security Machine Learning jobs in Portland, OR? For Remote Cyber Security Machine Learning jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Remote Cyber Security Machine Learning jobs in Portland, OR look for? The top searched job categories for Remote Cyber Security Machine Learning jobs in Portland, OR are:
Remote Cyber Security Machine Learning jobs near you
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Portland, OR • Remote

$50 - $90/hr

Part-time

Posted 11 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.

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