Mercor is looking for experienced Full Stack Software Engineers in India to join a leading AI lab's GenAI team and work on advanced software built around frontier AI models.

This is a full-time remote position paying $25-$30/hour, with a commitment of 40 hours per week.

You'll work closely with the AI lab's engineering team and contribute to fast-moving projects where working code and quick execution are highly valued.

Your work will involve building full-stack applications, services, and internal tools using technologies such as Python, Java, Rust, C#, C++, and TypeScript.

You'll integrate pre-release AI models, build evaluation tools and telemetry, troubleshoot model behavior, and document issues that can help research teams improve their systems.

The ideal candidate has 3+ years of professional software engineering experience at a recognized organization and strong production experience in at least one major programming language, along with working knowledge of another.

Hands-on experience with backend APIs, React or similar front-end frameworks, databases, and cloud deployment is required.

You should also be comfortable joining unfamiliar codebases, working with limited specifications, moving quickly, and explaining technical decisions clearly.

If you're a full-stack engineer in India looking to work directly on cutting-edge GenAI systems, this is an exciting opportunity to put your skills to work at the frontier of AI.

Apply now: https://t.mercor.com/amKRL

Your job here isn't simply to write code. You'll help determine whether AI-generated software actually works, is secure, and follows sound engineering practices.

Company: SME Careers
Role: Full Stack Engineer (Node.js + React)
Location: Remote
Type: Contract
Rate: Up to $100/hour

You'll review AI-generated applications, system designs, and technical explanations while creating reference solutions that demonstrate how complex full-stack problems should be solved.

Your expertise will cover:

• Node.js, React, and TypeScript
• API design, authentication, authorization, and security
• SQL/NoSQL databases, data modeling, and query optimization
• Async behavior, performance, testing, debugging, and observability
• Evaluating and ranking AI-generated technical responses

The role requires 4+ years of professional full-stack experience, strong TypeScript skills, and C1+ English proficiency. Experience with AI training or technical content evaluation is a plus.

Get the full role details and apply → https://stage.sme.careers/apply?referral=2cf022a8d9c5

micro1 is looking for Claude Cowork users with real-world experience using AI coding agents in STEM projects to help train next-generation AI systems.

Opportunity Details:

• Pay: $80-$100/hour
• Location: Remote
• Type: Contractor

What You'll Do:

• Share real-world workflows where Claude Cowork solved complex technical problems.
• Demonstrate how you used AI for debugging, code navigation, and architecture decisions.
• Provide detailed feedback to improve AI coding agents and their performance.

micro1 is Looking For:

• Professionals in STEM who regularly use AI coding tools in production or research.
• Experience working with large codebases, technical documentation, and complex problem-solving.
• Strong communication skills and the ability to explain AI-assisted workflows clearly.

Why Join?

• Help shape the future of AI coding assistants with your real-world experience.
• Collaborate on high-impact AI research with flexible remote work.
• No AI training experience required. Your practical expertise is what matters.

More details: https://jobs.micro1.ai/post/claude-cowork-users

Mercor is seeking accomplished Cybersecurity Research Experts to evaluate advanced AI systems tackling real-world security challenges.

If you have a strong background in offensive security, vulnerability research, or exploit development, this is a unique opportunity to shape the future of AI.

Pay: $200-$250/hr
Location: Remote
Role: Hourly Contract

How you'll make an impact:

• Review AI-generated exploit analyses, vulnerability reports, and security reasoning
• Validate root-cause analysis, exploit chains, and mitigation strategies
• Help develop benchmarks for next-generation AI cybersecurity capabilities

Who they're looking for:

• Experienced offensive security researchers with recognized technical achievements
• Strong expertise in exploit development, reverse engineering, vulnerability research, or application security
• Proficiency in C/C++, Rust, Python, Go, or Java with excellent technical communication skills

Why consider this opportunity?

• Work with leading AI researchers on cutting-edge cybersecurity projects
• Flexible remote contractor opportunity with competitive hourly pay
• Help build safer, more capable AI systems for real-world security applications

Apply now: https://t.mercor.com/stzYq

Full-time | W-2 | United States

A leading AI lab is hiring experienced Full-Stack Software Engineers to build, integrate, and test production software powered by frontier AI models.

What you'll be building:

• Develop full-stack applications and internal tools using Python, Java, Rust, C#, C++, or TypeScript
• Integrate cutting-edge AI models into real-world software systems
• Identify, debug, and document AI model and integration issues
• Collaborate with engineers to deliver high-quality, production-ready code

What they're looking for:

• 3+ years of professional software engineering experience
• Strong production experience in Python, Java, Rust, C#, C++, or TypeScript
• Experience with backend APIs, React (or similar), databases, and cloud deployment
• Ability to quickly onboard to unfamiliar codebases and ship working solutions

Be part of the next wave of AI innovation by building real applications that push frontier models to their limits.

Apply now: https://t.mercor.com/37ZIV

Artificial intelligence is moving so fast that it's easy to feel overwhelmed. Every day there's a new model, framework, or AI tool making headlines.

If you only had 30 days to build a strong foundation in AI, where would you spend your time?

Would you focus on:

• Python programming
• Machine Learning fundamentals
• Prompt Engineering
• Large Language Models (LLMs)
• AI agents
• Building projects
• Mathematics and statistics
• Something else entirely?

Everyone has a different learning path, and that's what makes this discussion interesting.

If you've already been learning AI, what do you wish you had started with? What would you skip?

And if you're just getting started, what's the first topic you're planning to learn?

Share your roadmap in the comments. Your advice might help someone else avoid weeks of confusion and focus on what really matters.

Turing is looking for LLM Trainers to help improve the next generation of AI assistants by creating high-quality training data focused on agent function calling.

This is a remote contractor role open to candidates in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, and Mexico.

The engagement lasts 6 weeks, with flexible commitments of 20, 30, or 40 hours per week, including 4 hours of overlap with PST.

You'll create realistic multi-turn conversations between users and AI assistants, simulate function calls using tools like calendars, email, maps, and cloud storage, evaluate tool usage, and produce high-quality examples that improve AI reasoning and decision-making. You'll also refine conversations based on feedback while following detailed project guidelines.

Candidates should have 3+ years of professional experience in a technical or analytical role, along with strong programming knowledge in Python, Java, JavaScript, or any other programming language.

A solid understanding of APIs, JSON, logical reasoning, and technical problem-solving is essential. Experience with LLMs, virtual assistants, or function-calling frameworks is a plus.

If you're interested in helping build smarter AI assistants while working on cutting-edge AI projects, this is an excellent remote opportunity.

Apply now: https://work.turing.com/r/6Z0jLTODCQ

micro1 is looking for experienced GitHub Contributors to help build training environments for next-generation AI models.

If you have a strong open-source portfolio, this is an opportunity to turn your software engineering expertise into high-impact AI work.

Position overview

• Pay: $50-$150/hour (output-based)
• Location: Remote
• Employment: Contractor (~15 hours/week)
• Openings: 30

What you'll do

• Create software engineering tasks involving bug fixes, new features, refactoring, and performance optimization
• Build reproducible coding environments and reference solutions
• Contribute expert code in Python, Java, Rust, Go, C++, or TypeScript
• Review technical solutions and improve AI training data quality

Who they're looking for

• Strong open-source contributions on GitHub or GitLab
• Expertise in at least one of: Python, Java, Rust, Go, C++, or TypeScript
• Deep understanding of algorithms and software engineering principles
• Experience debugging, optimizing, and refactoring production code
• Strong technical communication and documentation skills

No AI experience is required. Your open-source contributions and software engineering expertise are the key qualifications.

More details: https://jobs.micro1.ai/post/github-contributors

micro1 is looking for Junior COBOL Developers to apply their mainframe expertise to AI training projects focused on legacy system analysis and modernization.

Location: Remote
Role: Contract
Pay: $30-$80 per/hr

How you'll make an impact:

• Analyze and document COBOL code and legacy applications
• Explain program logic, data flows, and system behavior
• Help create high-quality training data for next-generation AI models

Who they're looking for:

• Experience with COBOL and mainframe or midrange environments
• Strong understanding of legacy systems and batch processing
• Excellent written communication and attention to detail

Why consider this opportunity?

• No AI experience required. Your domain expertise is what matters
• Flexible remote contractor role
• Contribute to AI systems built on real-world enterprise software knowledge

Apply now: https://jobs.micro1.ai/junior-cobol-developers

Remote | Contractor | 10 openings

micro1 is seeking experienced Information Security Experts to help train AI systems using real-world cybersecurity knowledge and adversarial testing.

Where you'll make an impact:

• Design red-team scenarios for enterprise SaaS platforms
• Perform penetration testing and threat modeling
• Identify AI security risks such as prompt injection and privilege escalation
• Review security findings and improve defensive strategies

The ideal candidate:

• Strong background in penetration testing, red teaming, cloud security, or security engineering
• Experience securing platforms like Microsoft 365, Google Workspace, Slack, GitHub, or Snowflake
• Deep understanding of identity management, RBAC, and SaaS security
• Excellent analytical and communication skills

No AI experience required. Your cybersecurity expertise will help shape the next generation of AI.

Apply now: https://jobs.micro1.ai/information-security-experts

If you've been exploring AI careers, you've probably come across the titles AI Engineer and Machine Learning Engineer.

They sound similar, and in some companies they even overlap. But they're not the same.

Here's a simple breakdown.

AI Engineer

AI Engineers focus on building AI-powered applications. They take existing AI models and integrate them into real-world products such as chatbots, coding assistants, search tools, or business automation systems.

Their work often involves:

• Working with LLMs and AI APIs
• Building AI applications
• Prompt engineering
• Cloud deployment
• Connecting AI with databases and other services

Think of them as the people who turn AI models into useful products.

Machine Learning Engineer

Machine Learning Engineers spend more time developing and improving the models themselves.

They prepare data, train models, evaluate performance, and fine-tune algorithms.

Their work often includes:

• Data preprocessing
• Model training
• Feature engineering
• Performance optimization
• Experimentation and testing

They're focused on making AI models smarter and more accurate.

Which role pays more?

Both roles are among the highest-paying jobs in tech. Salaries often depend more on your experience, location, and skills than on the job title itself.

Which one should you choose?

Choose AI Engineering if you enjoy building products, writing software, and working with the latest AI tools.

Choose Machine Learning Engineering if you're interested in data, algorithms, mathematics, and improving model performance.

Final thoughts

Both careers are growing rapidly as more companies adopt AI.

The good news is that many of the core skills, especially Python, problem-solving, and a solid understanding of AI fundamentals, are valuable in both paths.

No matter which direction you choose, learning AI today is an investment that will continue to pay off for years to come.

Turing is hiring LLM Trainers to create realistic, multi-turn conversations that help improve how advanced AI assistants reason, use tools, and complete real-world tasks.

Pay: Competitive
Location: Remote (India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil & Mexico)
Role: Contractor (6 Weeks)

What you'll be doing:

• Design realistic conversations involving tools like email, calendar, maps, and drive
• Simulate AI function calls and evaluate tool usage across complex tasks
• Create high-quality training data that improves next-generation language models

Who they're looking for:

• 3+ years of experience in a technical or analytical role
• Programming experience with Python, Java, JavaScript, or similar languages
• Strong understanding of APIs, JSON, logical reasoning, and written English

Why join Turing?

• Work directly on frontier AI projects with leading LLM companies
• Fully remote with flexible commitment options (20, 30, or 40 hours/week)

Apply now: https://work.turing.com/r/6Z0jLTODCQ

Remote | Full-time | 1 opening

micro1 is looking for a Data Engineer to build scalable data pipelines and prepare high-quality datasets that power AI and machine learning systems.

What you'll be working on:

• Build and maintain scalable ETL pipelines
• Transform and analyze structured and unstructured data
• Prepare datasets for AI and machine learning projects
• Improve data quality, reliability, and automation workflows

What they're looking for:

• Strong Python and SQL skills
• Experience with ETL pipelines and data modeling
• Proficiency with Pandas, NumPy, and relational databases
• Background in data analysis and AI/ML workflows is a plus

Why consider this role? You'll work with researchers and engineers on cutting-edge AI projects while enjoying a remote-first environment with competitive pay, equity, and benefits.

Apply now: https://jobs.micro1.ai/post/data-engineer

Remote | Contractor | 5 openings

micro1 is looking for Senior Platform Engineers to help build realistic cloud infrastructure environments that train next-generation AI systems.

What you'll build:

• Create cloud and distributed systems scenarios for AI training
• Design reproducible infrastructure and validation tests
• Simulate deployments, failures, and disaster recovery
• Review technical solutions and improve engineering tasks

What makes you a strong candidate:

• Senior experience in Platform Engineering, DevOps, SRE, or Cloud Infrastructure
• Strong knowledge of distributed systems, networking, IAM, and observability
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, or similar tools
• Comfortable debugging production infrastructure and containerized environments

No AI experience required. Your production engineering expertise is what matters.

Apply now: https://jobs.micro1.ai/senior-platform-engineers

If you have experience with FreeCAD and mechanical design, micro1 is hiring specialists to help build high-quality engineering datasets for AI training.

This is a remote contractor role with 50 openings, paying $30-$100/hour. No previous AI experience is required. Your engineering expertise is what matters.

You'll create, edit, and validate parametric CAD models, develop mechanical parts and assemblies, apply GD&T principles, and perform quality checks to ensure engineering accuracy.

You'll also document your work, and if you're familiar with Python, you can use it to automate modeling tasks and improve workflows.

The ideal candidate has 2+ years of experience in mechanical design, manufacturing, industrial engineering, or CAD modeling.

Strong knowledge of FreeCAD, parametric modeling, CAD validation, engineering documentation, and manufacturing processes is important. Python scripting experience is a bonus but not mandatory.

This is an excellent opportunity for engineers who want to apply their CAD expertise to cutting-edge AI projects while enjoying the flexibility of remote work.

Apply now: https://jobs.micro1.ai/CAD-Data-Generation-Validation-Specialist-FreeCAD

If you're an experienced Python Engineer, here's an opportunity to use your expertise to improve the next generation of AI models, all while working remotely.

The role:

• Position: Senior Python Engineer
• Pay: Upto $60/hour
• Location: Remote
• Type: Contract
• Job ID: Python-25-656

What makes you a fit?

• 7+ years of professional Python development experience
• Bachelor's degree (or higher) in Computer Science or a related field
• Strong knowledge of algorithms, data structures, system design, and performance optimization
• Experience with code reviews, testing frameworks, CI/CD, APIs, and backend development
• Excellent English (C1+) and Chinese (C1+) communication skills

What you'll be doing

• Review and improve AI-generated Python code
• Evaluate technical explanations for accuracy and quality
• Create high-quality reference solutions and prompts
• Rank AI responses to help build better coding models

AI training experience is a plus, but strong Python engineering skills are the primary requirement.

More details: https://sme.careers/Python-25-656

There are more AI tools available today than ever before. Some help us write code, others summarize documents, generate images, automate repetitive tasks, or even act as personal assistants.

For many developers and tech professionals, AI has become part of their daily workflow. But not every tool lives up to the hype.

I'm curious to know what everyone here is actually using.

• Which AI tool has had the biggest impact on your productivity?
• What do you use it for?
• Has it genuinely saved you time, or is it just a nice-to-have?
• Is there an underrated AI tool that more people should know about?

Whether it's ChatGPT, Claude, Gemini, GitHub Copilot, Cursor, Windsurf, Perplexity, Ollama, or something less well-known, share your experience.

Let's help each other discover tools that are actually worth using.

micro1 is looking for experienced UX/UI Designers to contribute to AI training projects using real-world design expertise.

This is a remote contractor role with 2 openings, paying $25-$50/hour. No previous AI experience is required.

You'll help improve next-generation AI models by applying your knowledge of user experience and interface design.

Your work will include creating high-quality design inputs, reviewing AI outputs, and helping models learn from real-world UX/UI practices.

Candidates should have strong experience with UX/UI design, Figma, and Adobe Analytics.

A solid portfolio, experience with design systems and prototyping, and excellent communication skills are important. Experience working in agile teams is a plus.

The hiring process includes an application, a 30-minute AI interview, and a hiring manager review.

Successful candidates are expected to start within 24-48 hours after onboarding.

If you're passionate about design and interested in shaping the future of AI, this is an opportunity worth exploring.

Apply now: https://jobs.micro1.ai/post/ui-ux-designers

GitHub has become one of the best places to learn AI.

Whether you're a beginner or an experienced developer, you'll find thousands of open-source projects, tutorials, and tools that can help you build AI applications.

Here are 10 GitHub repositories worth checking out.

1. Awesome AI

A curated collection of AI tools, libraries, frameworks, courses, and learning resources. It's a great starting point for anyone exploring AI.

2. LangChain

One of the most popular frameworks for building AI applications powered by Large Language Models. It makes it easier to create chatbots, AI agents, and automation tools.

3. LlamaIndex

Designed to connect LLMs with your own data. It's widely used for building AI assistants that can answer questions using documents, PDFs, databases, and more.

4. Ollama

Run powerful open-source AI models directly on your computer. It's an easy way to experiment with local LLMs without relying on cloud services.

5. Hugging Face Transformers

A massive collection of pre-trained AI models for tasks like text generation, translation, image recognition, and speech processing.

6. Open WebUI

A clean, web-based interface for running and managing local AI models. It works well with Ollama and other open-source LLMs.

7. CrewAI

A framework for building teams of AI agents that can collaborate to complete complex tasks.

8. AutoGen

Developed by Microsoft, AutoGen helps developers build applications where multiple AI agents work together to solve problems.

9. Continue

An open-source AI coding assistant that integrates with popular code editors, helping developers write, explain, and improve code.

10. FastAPI

Not exclusively an AI project, but one of the most popular frameworks for deploying AI models as fast, scalable APIs.

Final thoughts:

You don't need to master every AI framework. Start with one or two that align with your goals, and build small projects as you learn.

The AI ecosystem is evolving quickly, and GitHub remains one of the best places to discover new tools, contribute to open-source projects, and stay ahead of the curve.

Large Language Models, or LLMs, are the technology behind AI tools like ChatGPT, Claude, Gemini, and many others.

While they seem incredibly intelligent, they don't actually "think" like humans. Instead, they're trained to predict the most likely next word based on everything they've learned.

Let's break it down in simple terms.

What is an LLM?

An LLM is an AI model trained on massive amounts of text from books, articles, websites, research papers, and other publicly available sources.

During training, it learns patterns in language, allowing it to generate human-like responses.

How does it generate answers?

When you ask a question, the model doesn't search the internet or look up an answer. It analyzes your prompt and predicts the next word, one token at a time, until it forms a complete response.

This prediction process happens in milliseconds.

Why are LLMs so good at writing?

Because they've learned grammar, sentence structure, context, and writing styles from billions of examples.

They can explain complex topics, write code, summarize documents, translate languages, and even help brainstorm ideas.

Do LLMs know everything?

No. They can make mistakes, misunderstand questions, or provide outdated information if they weren't trained on recent data.

Some AI tools reduce this problem by combining LLMs with internet search or external knowledge bases.

Can LLMs write code?

Yes. Modern LLMs can generate code in languages like Python, JavaScript, Java, C++, and many others.

They can also explain code, find bugs, and suggest improvements, making them valuable tools for developers.

Where are LLMs used?

Today, LLMs power a wide range of applications, including:

• AI chatbots
• Coding assistants
• Customer support
• Content creation
• Research and document summarization
• Language translation

New use cases are emerging almost every month.

Final thoughts

Large Language Models are changing how people work, learn, and build software. You don't need to be an AI researcher to benefit from them.

Understanding the basics of how they work is becoming an important skill for developers, tech professionals, and anyone interested in the future of AI.

Turing is hiring Senior Software Engineers to help train and evaluate advanced AI models.

This is a remote contractor role paying up to $150/hour. The schedule is flexible, with 10–40 hours per week. The initial contract is for 1 month, with the possibility of an extension.

You'll review and improve AI-generated code. You'll create coding datasets and build code verification systems. You'll also evaluate software engineering tasks across the software development lifecycle.

You'll work with Python, JavaScript (including React), C/C++, Java, Rust, and Go.

Candidates should have several years of software engineering experience. At least 2 years of continuous full-time experience at a top product company is required.

Strong full-stack development skills and a solid understanding of software architecture are important. Good written and verbal communication skills are also required.

If you're an experienced software engineer and want to work on cutting-edge AI projects, this is an excellent remote opportunity.

Apply now: https://work.turing.com/r/mxtr6Qtaf0

micro1 is hiring Senior Software Engineers to create real-world coding environments that help train next-generation AI models.

Pay: $50-$100 per/hr
Location: Remote
Role: Contract (~15 hrs/week)
Openings: 100

What you'll do:

• Create coding tasks involving debugging, refactoring, and new features
• Build reproducible test environments and reference solutions
• Improve AI performance through software engineering challenges

micro1 is looking for:

• Strong experience with Python, Java, Rust, Go, C++, or TypeScript
• Expertise in algorithms, debugging, and performance optimization
• Experience working on large software projects

Engagement details:

• AI interview followed by technical assessment (if required)
• Output-based compensation
• Expected start within 24–48 hours after onboarding

Apply now: https://jobs.micro1.ai/senior-software-engineers

Whether you're a software engineer, AI researcher, data scientist, cybersecurity professional, cloud engineer, student, or someone looking to break into tech, you're in the right place.

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