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Temporary Remote Ai Engineer Jobs in Decatur, GA

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

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 ...

New

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 ...

New

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... engineering, DFIR, malware analysis, threat intelligence, or adjacent fields, including government ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... other engineers -- who are driving real-world impact in AI development. Our platform offers an ...

SDLC Engineer - AI Trainer

Atlanta, GA ยท Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... other engineers -- who are driving real-world impact in AI development. Our platform offers an ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... other engineers -- who are driving real-world impact in AI development. Our platform offers an ...

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Showing results 1-20

Temporary Remote Ai Engineer information

See Decatur, GA salary details

$35.1K

$94.7K

$145K

How much do temporary remote ai engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for temporary remote ai engineer in Decatur, GA is $94,675.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $107,400.00 per year, depending on experience, location, and employer.

What are Temporary Remote AI Engineers?

Temporary Remote AI Engineers are professionals hired on a short-term contract to develop, implement, or maintain artificial intelligence systems while working remotely. They typically work for a set period, such as a few months, and may assist companies with specific AI projects, model training, or data analysis. Their remote setup allows organizations to access specialized AI talent without geographic limitations, making it easier to scale teams quickly for time-sensitive tasks.

What is the difference between Temporary Remote Ai Engineer vs Temporary Remote Data Scientist?

AspectTemporary Remote Ai EngineerTemporary Remote Data Scientist
Required CredentialsBachelor's or higher in CS, AI, or related; experience with AI frameworksBachelor's or higher in CS, Statistics, or related; experience with data analysis tools
Work EnvironmentRemote, project-based, AI development teamsRemote, data analysis projects, research teams
Employer & Industry UsageTech companies, AI startups, R&D labsTech firms, finance, healthcare, research institutions
Common Search & ComparisonYesYes

Temporary Remote Ai Engineers focus on developing and implementing AI models and algorithms, often requiring programming skills and knowledge of AI frameworks. Temporary Remote Data Scientists analyze data to extract insights, requiring statistical and analytical expertise. Both roles are remote, project-based, and prevalent in tech industries, but they differ in their core responsibilities and skill sets.

What are some common challenges faced by Temporary Remote AI Engineers, and how can they overcome them?

Temporary Remote AI Engineers often encounter challenges such as quickly adapting to new codebases, collaborating with distributed teams across time zones, and accessing necessary data or computing resources remotely. To overcome these, it's important to communicate proactively with team members, familiarize yourself with company documentation and tools early on, and set clear expectations about deliverables and timelines. Leveraging collaborative platforms like Slack, GitHub, or JupyterHub can also facilitate smoother workflow and integration with the team.

What are the key skills and qualifications needed to thrive as a Temporary Remote AI Engineer, and why are they important?

To thrive as a Temporary Remote AI Engineer, you need a solid background in computer science, machine learning, and programming languages like Python, often supported by a relevant degree or equivalent experience. Familiarity with AI frameworks such as TensorFlow or PyTorch, cloud platforms, and version control systems is typically required. Strong problem-solving abilities, self-motivation, and effective virtual communication are vital soft skills for remote collaboration and project delivery. These skills and qualities enable efficient development, deployment, and teamwork in a remote setting, ensuring successful project outcomes.
What are popular job titles related to Temporary Remote Ai Engineer jobs in Decatur, GA? For Temporary Remote Ai Engineer jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Temporary Remote Ai Engineer jobs in Decatur, GA look for? The top searched job categories for Temporary Remote Ai Engineer jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Temporary Remote Ai Engineer jobs? Cities near Decatur, GA with the most Temporary Remote Ai Engineer job openings:
Infographic showing various Temporary Remote Ai Engineer job openings in Decatur, GA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $94,675 per year, or $45.5 per hour.
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Atlanta, GA โ€ข 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 โ€” 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 communityโ€”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.