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Remote Cyber Security Machine Learning Jobs in Tennessee

ITR

Senior Azure Cloud Engineer

Oak Ridge, TN · Remote

$53.25 - $71.25/hr

... services, Azure Machine Learning, Azure OpenAI, and Terraform * Implement and maintain ... Coordinate with networking, cybersecurity, and application teams to ensure Azure environments are ...

Relativity

Principal Applied Scientist

Nashville, TN · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

Xsolis

Senior Cloud Security Engineer

Franklin, TN · On-site +1

$110.40K - $151.40K/yr

... Machine Learning (ML), and Generative AI. Security, privacy, and trust are foundational for ... Master's degree in Cybersecurity, Computer Science, or Information Systems degree desirable

Revecore

Senior Data Engineer

Franklin, TN · Remote

$102.20K - $138.90K/yr

Remote-USA Revecore is embarking on re-architecting and modernizing its core platform. The Data ... This team is composed of Data Engineering, Analytics Engineering, Data Science and Machine Learning ...

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Remote Cyber Security Machine Learning information

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.

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 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.

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 are popular job titles related to Remote Cyber Security Machine Learning jobs in Tennessee? For Remote Cyber Security Machine Learning jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Remote Cyber Security Machine Learning jobs in Tennessee look for? The top searched job categories for Remote Cyber Security Machine Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Remote Cyber Security Machine Learning jobs? Cities in Tennessee with the most Remote Cyber Security Machine Learning job openings:
Remote Cyber Security Machine Learning jobs near you
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Chattanooga, TN • Remote

Other

Posted 7 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply