Technology Job Trends in February 2025

This month: Small Language Models, Hugging Face Spaces, LangFuse, and more!

Author

Remco Strijdonk
February 10, 2025

Hello there, and welcome to our ninth monthly Job Trends newsletter!

New Month = New API?
Introducing our Hiring Manager API!

This API returns jobs + a hiring manager's Email Address / LinkedIn profile

Great for lead gen!

What else is new?
I have big plans for Job.zip in 2025, you can expect a completely different platform in the next couple of months (if I finally get some time off from the APIs). Stay tuned!

Access our Job Data

Are you starting a job board, enriching your AI, or anything else that could use our 10 million+ monthly jobs?

Enrich your job data with one of our self-serve APIs:

Job.zip’s data is supplied by Fantastic.jobs. If you’re interested in learning more or looking for a custom solution? Let’s chat! Please respond to this email or schedule a call

These roles and industries appeared in jobs for the first time during the last 12 months:

A cloud-based platform by Hugging Face for hosting and sharing machine learning models and applications. It enables developers to easily showcase, test, and deploy AI models with minimal setup.

A cybersecurity company focused on data security and privacy, offering solutions for data protection and compliance.

A vector database designed for complex data retrieval and analysis. Used extensively in applications that require high-performance data science capabilities.

Growing strong

These Trends are on the way up year over year:

DSPy is an open-source framework that helps developers build and fine-tune applications using large language models (LLMs). Instead of manually crafting prompts for the AI, DSPy allows you to write high-level code with natural language annotations, which it then compiles into the detailed instructions the model needs. This approach simplifies the development process and makes it easier to manage complex AI systems.

Langfuse is an open-source tool that helps developers build and improve applications powered by large language models (LLMs). Think of it as a toolkit that provides insights into how these AI models operate within an application, making it easier to identify and fix issues.

One of Langfuse's main features is its ability to monitor the different steps an AI model takes to generate a response. This monitoring helps developers understand the model's behavior and troubleshoot any problems that arise. Additionally, Langfuse offers tools to manage and test the prompts (questions or tasks) given to the AI, ensuring that the model's outputs are accurate and relevant.

From LLM to SLM? Small Language Models are taking over! With fewer resources and shorter time to results, SLMs offer enhanced efficiency, cost-effectiveness, and improved data privacy.

SLMs are designed with fewer parameters and simpler architectures, resulting in faster training times, reduced energy consumption, and the ability to operate on devices with limited computational resources.

This efficiency lowers operational costs and minimizes the environmental impact associated with large-scale AI deployments. What’s not to like?

That’s it for now, thanks for reading!

Any feedback? Respond to this mail!