Artificial Intelligence - Projects & Jobs

Check out Sample Remote Projects & Remote Jobs Posted in AiDOOS

Visual Media Annotation Expert

Seeking a Video Captioning AI Data Trainer for remote position.

Annotate video clips with focus, action, and camera movements.

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Rust Engineering Lead

Seeking Rust Engineering Leads for adopting Rust and rethinking foundations of Linux syste

Responsible for designing and implementing well-tested and documented software in Rust.

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VP of Financial Operations

Requires 5+ years experience in operations management and strong communication and leaders

Company values transparency, merit-based culture, and delivering exceptional service and r

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Compliance Specialist

Compliance Specialist for Monitor Liaison Office (MLO)

Perform compliance & assurance reviews on monitor requests

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Kernel Developer

Remote Kernel Developer with expertise in C programming and Linux kernel core subsystems.

Provide support for existing functionality and implement new features.

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Engineering Director

Director of Engineering for Product Foundations team at VRChat.

Lead team of 15 engineers to build technical foundation for VR platform.

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HALTE Community & Chatbot

Development of “HALTE Community” on opensource “Discource” platform Building AI Bot bas

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AWS Hosting

Deploy new AI Workloads - Migrate existing AI workloads from Azure to AWS - Migration of M

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PeopleChain

1. Develop a solution for managing the functional history of people within an organization

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AI-driven real-estate platform

• Develop and implement AI-driven solutions to provide personalized insights for real esta

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AiDOOS SEO

• Identify and develop SEO strategies to improve website visibility and organic rankings.

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AiDOOLOGY

AiDOOS Methodology, referred to as AiDOOLOGY, forms the bedrock of AiDOOS by outlining the systematic approach to platforming services and knowledge-based tasks. Brilliant minds spanning the globe collaborate, forming teams to provide enterprises with exceptional solutions, all within a straightforward, streamlined, secure, and dependable process.

What is Artificial Intelligence?

Artificial Intelligence (AI) is a branch of computer science that focuses on building intelligent machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Technologies used in Artificial Intelligence

Some of the technologies that are used in AI include:

  • Machine learning
  • Deep learning
  • Natural language processing
  • Computer vision
  • Expert systems
  • Robotics

How to become an expert in Artificial Intelligence?

To become an expert in AI, you need to have a strong foundation in computer science and mathematics. Some of the skills required include:

  • Programming languages: Python, R, Java, C++, etc.
  • Mathematics: Linear algebra, calculus, probability, statistics
  • Machine learning algorithms and techniques
  • Natural language processing
  • Deep learning frameworks like TensorFlow and PyTorch

There are several online courses, bootcamps, and degree programs that can help you get started with AI. Some of the resources include:

  • Coursera: Machine Learning and Deep Learning Specializations
  • edX: Artificial Intelligence MicroMasters Program
  • Udacity: AI Nanodegree Programs
  • Google AI Education
  • Microsoft AI School

Opportunities in Artificial Intelligence

AI is one of the fastest-growing fields with a wide range of job opportunities. Some of the career paths include:

  • Data scientist
  • Machine learning engineer
  • AI researcher
  • Natural language processing engineer
  • Computer vision engineer
  • Robotics engineer

Various Aspects of Artificial Intelligence

Some of the various aspects of AI include:

  • Ethics: As AI becomes more powerful, it raises important ethical questions about its use and impact on society.
  • Explainability: As AI systems become more complex, it becomes harder to explain how they make decisions.
  • Deployment: Deploying AI systems at scale requires careful planning, testing, and monitoring to ensure they work as intended.
  • Scaling: AI systems are highly data-driven and require large amounts of data to train and improve performance.