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Remote Machine Learning Postdoc Jobs in Kentucky

Data Engineer (Remote)

Louisville, KY · On-site +1

$104K - $125K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ML workflows (e.g., batch/real-time scoring) * Continually improve ongoing reporting and analytics ...

Data Engineer (Remote)

Louisville, KY · On-site +1

$104K - $125K/yr

Support deployment and operationalization of machine learning models by integrating pipelines with ML workflows (e.g., batch/real-time scoring) * Continually improve ongoing reporting and analytics ...

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

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 ...

$94K - $113K/yr

Familiarity with big data technologies, machine learning, and data analysis preferred. * Experience ... Remote apply for this job

$94K - $113K/yr

Familiarity with big data technologies, machine learning, and data analysis preferred. * Experience ... Remote apply for this job

Exposure to AI technologies, such as machine learning, natural language processing, and data ... Remote NY will be considered, preferred is DC Metro and Louisville, KY. Travel : Occasional travel ...

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Remote Machine Learning Postdoc information

Is ML a high paying job?

Machine learning postdoctoral positions are generally well-paid compared to many academic roles, with salaries often ranging from $60,000 to over $100,000 annually depending on experience, location, and funding. These roles typically require strong programming skills in Python or R and knowledge of algorithms and data analysis, which can contribute to higher compensation levels.

Is a PhD in ML worth it?

A PhD in machine learning can enhance qualifications for a remote machine learning postdoc position, often leading to higher-level research opportunities and increased earning potential. However, it requires significant time investment and may not be necessary for industry roles that value practical skills and experience with tools like Python and TensorFlow. The decision depends on career goals and the specific requirements of the desired position.

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

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

Is a postdoc harder than a PhD?

A remote machine learning postdoc typically involves more specialized research, higher expectations for independence, and often requires advanced skills in programming and data analysis. While a PhD focuses on completing a dissertation and gaining foundational expertise, a postdoc emphasizes producing publishable research and may involve longer hours and greater responsibility, making it generally more demanding in terms of research output and expertise. However, the difficulty varies based on individual experience and research environment.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

Do you need H-1B for postdoc?

A remote machine learning postdoctoral position typically does not require H-1B sponsorship if the candidate is already authorized to work in the country, such as through a visa or citizenship. However, international candidates may need H-1B or other work visas depending on the employer and local immigration laws. Employers often sponsor visas for postdocs to comply with legal requirements and facilitate employment.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
What are the most commonly searched types of Machine Learning Postdoc jobs in Kentucky? The most popular types of Machine Learning Postdoc jobs in Kentucky are:
What are popular job titles related to Remote Machine Learning Postdoc jobs in Kentucky? For Remote Machine Learning Postdoc jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Kentucky look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Kentucky are:
What cities in Kentucky are hiring for Remote Machine Learning Postdoc jobs? Cities in Kentucky with the most Remote Machine Learning Postdoc job openings:
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Louisville, KY • Remote

$50 - $90/hr

Part-time

Posted 12 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.