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Machine Learning Ai Developer Jobs in Kentucky (NOW HIRING)

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AI Security Architect - Erlanger, KY

Erlanger, KY

$92K - $172K/yr

... Engineering/Analyst background. This role safeguards enterprise AI systems by applying Industry ... The role proactively identifies and mitigates risks from adversarial machine learning, data ...

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Machine Learning Ai Developer information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence or machine learning, such as senior AI researcher, lead data scientist, or AI architect, often requiring advanced skills, extensive experience, and expertise in tools like Python, TensorFlow, or PyTorch. Such roles usually involve strategic decision-making, innovation, and leadership in AI projects, and they tend to be found in large tech companies or specialized research organizations. Compensation at this level reflects the complexity and impact of the work, along with responsibilities like managing teams or developing cutting-edge AI solutions.

What engineer makes $500,000 a year?

Senior machine learning AI developers with extensive experience, advanced skills in deep learning, and proficiency in tools like TensorFlow or PyTorch can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Such roles often require advanced degrees, certifications, and a strong track record of impactful projects.

What is the difference between Machine Learning Ai Developer vs Data Scientist?

AspectMachine Learning Ai DeveloperData Scientist
CredentialsBachelor's or higher in CS, AI, or related fields; certifications in ML/AIBachelor's or higher in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops AI models, algorithms, and applications; often in tech companies or R&DAnalyzes data, builds models, and provides insights; in various industries including finance, healthcare
Industry UsagePrimarily in AI product development, software, and tech firmsAcross industries for data analysis, business intelligence, and decision-making

While both roles require knowledge of machine learning and programming, Machine Learning Ai Developers focus on creating and deploying AI models and applications, whereas Data Scientists analyze data to extract insights and inform business strategies. The roles often overlap but differ in primary focus and application.

What is the salary of AI ML developer?

The salary of a Machine Learning AI Developer varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually in many regions. Senior roles or those with specialized skills in deep learning, natural language processing, or cloud platforms can earn higher salaries, especially with certifications and advanced degrees.

Which 3 jobs will survive AI?

For a Machine Learning AI Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as data scientists, AI ethics specialists, and AI system architects. These positions involve tasks that are difficult to automate and often require advanced domain knowledge, critical thinking, and collaboration skills. Continuous learning and expertise in tools like Python, TensorFlow, or cloud platforms enhance job security in this field.
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What job categories do people searching Machine Learning Ai Developer jobs in Kentucky look for? The top searched job categories for Machine Learning Ai Developer jobs in Kentucky are:
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Machine Learning Ai Developer jobs near you
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Louisville, KY • Remote

$50 - $90/hr

Part-time

Posted 10 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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