The current AI job market is flooded with prompt engineers and individuals who have only ever interacted with an API. To break into Generative AI, you need to demonstrate that you’re not just a user, but a builder. Start building things that solve real problems and showcase skills companies are desperately looking for. So, in this article, I’ll give you some ideas to build Generative AI projects that will actually get you hired.
Fine-Tuning an LLM with LoRA for a Niche Task
Anyone can use a general-purpose model like GPT-4 or Gemini. But what companies really need are models that are experts in their specific domain, whether it’s understanding legal contracts, writing medical reports, or generating code in a proprietary programming language. This is where fine-tuning comes in, and it’s one of the most in-demand skills today.
Working on such projects proves you can take a powerful but generic model and specialize it efficiently. It will show you’re not just a consumer of AI; you’re tailoring it to solve a specific business problem.
Your goal in this project will be to fine-tune a powerful open-source model on a custom dataset using a technique called LoRA (Low-Rank Adaptation). Find a guided example of this project here.
Building a Multimodal AI Model
The world isn’t just text. It’s a rich tapestry of images, sounds, and words. The next frontier of AI is multimodality, the ability to understand and connect information from different sources, just like humans do. Building a model that can look at a picture and describe it, or read a question and find the answer in an image, puts you at the cutting edge.
Working on such projects shows you’re thinking beyond text-only models. You understand complex data pipelines and architectures, which is essential for building next-generation applications in everything from autonomous driving to medical diagnostics.
A great starting point is building a Visual Question Answering (VQA) or an Image Captioning model. Find a guided example to work on such projects here.
Building a Multi-Agent System using the Gemini API
We’re moving from AI models that just answer questions to AI agents that can perform tasks. An agent can reason, plan, and use tools (like searching the web, running code, or accessing other APIs). A multi-agent system is like hiring a team of specialized AI experts who collaborate to solve a complex problem. This is one of the hottest areas in AI right now.
Building an agent system shows you can think about AI in terms of workflows, autonomy, and problem decomposition. It’s a clear signal that you’re ready to build sophisticated applications that go far beyond simple text generation.
Your goal here is to create a system where multiple AI agents, each with a specific role, work together. Find a guided example to work on such projects here.
Building a Generative Model From Scratch to Generate Images
This is the ultimate challenge and the biggest differentiator. While the three projects above show you can use and adapt existing tools, this one proves you understand the fundamental principles from the ground up. If you can build a generative model from scratch, even a simple one, you’re in the top 1% of candidates.
Such projects show a testament to your deep understanding of the math, architecture, and training dynamics behind generative models. It shows you’re not afraid to get your hands dirty with the low-level details, a quality that is incredibly rare and valuable.
Here, you don’t need to build the next Stable Diffusion. The goal is to demonstrate your understanding by building a Generative Adversarial Network (GAN) or a simple Diffusion Model. Find a guided example of this project here.
Summary
So, here are some ideas to build Generative AI projects that will actually get you hired:
- Fine-Tuning an LLM with LoRA for a Niche Task
- Building a Multimodal AI Model
- Building a Multi-Agent System using the Gemini API
- Building a Generative Model From Scratch to Generate Images
I hope you liked this article on ideas to build Generative AI projects that will actually get you hired. Feel free to ask valuable questions in the comments section below. You can follow me on Instagram for many more resources.
