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Part Time Remote Machine Learning Jobs in Georgia

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 ...

Comfort with learning streamlined clinical technology * Strong clinical judgement, communication ... Full-time and part-time W-2 employment Total annual on-target earnings of $325k - $375k ...

Apply Early

Comfort with learning streamlined clinical technology * Strong clinical judgement, communication ... Full-time and part-time W-2 employment Total annual on-target earnings of $325k - $375k ...

Apply Early

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Part Time Remote Machine Learning information

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle some tasks, MLEs are essential for creating, tuning, and overseeing complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model optimization, and deployment remains critical in AI development environments.

How to make $1000 a week remotely?

A part-time remote machine learning role can generate $1000 weekly by working on high-demand projects, leveraging skills in programming, data analysis, and model development. Earning this amount typically requires consistent effort, specialized knowledge, and possibly multiple freelance or contract assignments, often with flexible schedules and the use of online platforms to find opportunities.

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

To thrive as a Part Time Remote Machine Learning professional, you need a strong grasp of mathematics, statistics, programming (commonly Python), and a relevant educational background such as a degree in computer science or a related field. Familiarity with machine learning frameworks (e.g., TensorFlow, scikit-learn, PyTorch) and version control systems like Git is typically required. Excellent time management, self-motivation, and clear communication skills are crucial for navigating remote collaboration and project deadlines. These skills ensure that you can independently deliver high-quality ML solutions while effectively contributing to distributed teams.

What are part time remote machine learning jobs?

Part time remote machine learning jobs are positions where professionals work on machine learning projects or tasks for a limited number of hours per week, and do so from a location outside the traditional office environment, often from home. These roles typically involve developing, testing, or deploying machine learning models, analyzing data, and collaborating with teams online. They are ideal for people seeking flexibility, such as students, freelancers, or individuals balancing other commitments, while contributing to projects in fields like AI, data science, or analytics.

How do part-time remote machine learning roles typically structure collaboration and communication with the rest of the team?

Part-time remote machine learning professionals often collaborate with teams using digital tools such as Slack, Zoom, and project management platforms like Jira or Trello. Regular check-ins, virtual stand-ups, and shared documentation ensure alignment on project goals and timelines despite differing work hours. Clear communication and proactive updates are important, as team members may be dispersed across time zones and working non-overlapping schedules. Flexibility and self-motivation are key to staying connected and contributing effectively in this distributed work environment.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and strong contributions to high-impact projects can earn salaries approaching or exceeding $500,000 annually, especially in top tech companies or through equity and bonuses. Such roles often require advanced degrees, specialized knowledge, and a track record of innovation in AI and data science.

What is the difference between Part Time Remote Machine Learning vs Part Time Remote Data Scientist?

AspectPart Time Remote Machine LearningPart Time Remote Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related field; knowledge of ML frameworksDegree in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentRemote, flexible hours, project-basedRemote, collaborative teams, project-focused
Industry UsageTech, finance, healthcare, e-commerceTech, finance, marketing, research
Common Search IntentPart Time Remote Machine Learning jobs, freelance ML rolesPart Time Remote Data Scientist jobs, freelance data roles

Part Time Remote Machine Learning roles focus on developing algorithms and models, often requiring programming and ML frameworks. Part Time Remote Data Scientist positions involve analyzing data, creating insights, and may include statistical analysis. Both roles are remote and flexible but differ in core responsibilities and skill sets.

How to make 2000 a week working from home?

A part-time remote machine learning role can potentially generate $2,000 weekly if you have advanced skills, relevant experience, and access to high-paying projects or freelance platforms. Building a strong portfolio, specializing in in-demand areas like deep learning or NLP, and leveraging platforms such as Upwork or Toptal can help achieve this income level. Consistent effort, continuous learning, and effective client management are essential for reaching such earnings.
What job categories do people searching Part Time Remote Machine Learning jobs in Georgia look for? The top searched job categories for Part Time Remote Machine Learning jobs in Georgia are:
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Atlanta, GA • Remote

$50 - $90/hr

Part-time

Posted 3 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.