engineering VS label-studio

Slim.AI | Fullstack and Backend Engineers | REMOTE, international or Seattle/Bellevue/WA | Full-time | Golang, Node.js, Vue.js/Nuxt.js

I'm the founder and CTO at Slim.AI. We are a well funded seed stage startup (9M+) in the developer tooling space. Our mission is to simplify and accelerate the containerized app delivery (it's too hard, too complicated and with too much manual work). We are about to transition to the next phase and we are expanding our engineering team.

Our engineering team is the innovation engine for our product because we are building a solution to solve our own problems creating and running containerized cloud-native applications.

We use Golang, Node.js Serverless/Lambda and containers. We have frontend, backend and fullstack roles ( https://github.com/slim-ai/engineering ).

Our engineering principles:

* We use what we build.

Slim.AI | Backend and Fullstack Engineers | REMOTE, international or Seattle/Bellevue/WA | Full-time | https://github.com/slim-ai/engineering

We are a well funded seed stage startup (9M+) in the developer tooling space on a mission to redefine how DevOps is done for containerized apps (it's too hard, too complicated and with too much manual work). We are about to transition to the next phase and we are expanding our engineering team.

Our engineering team is the innovation engine for our product because we are building a solution to solve our own problems creating and running containerized cloud-native applications.

We use Golang, Node.js Serverless/Lambda and containers. Take a look at the backend ( https://github.com/slim-ai/engineering/blob/master/roles/bac... ) and fullstack ( https://github.com/slim-ai/engineering/blob/master/roles/ful... ) roles and our engineering principles to see if the role and how we do engineering looks interesting to you ( https://github.com/slim-ai/engineering#engineering-principle... ).

Email me at [email protected] if you'd like to learn more.

P.S.

And take a look at DockerSlim ( https://github.com/docker-slim/docker-slim ) if you are interested in working on the open source project that powers our SaaS.

Slim.AI | REMOTE or Seattle | Full-time | Developer Experience Lead | https://github.com/slim-ai/engineering

Do you enjoy working with lots of different applications stacks? Do you like helping others? Do you want to build lots of different applications? Are you interested in contributing to open source?

We are a funded seed stage startup in the developer tooling and DevOps space empowering developers to build and run their cloud-native applications. The current product is focusing on containers and the friction around them.

We are building a brand new engineering team. We are developer friendly, low on process with no mind-numbing bureaucracy or micromanagement. We are looking for people who'll be excited to be a part of the engineering team in an early stage startup during its inception phase building modern cloud-native applications the right way.

You can find out more about the mission, how we work and the roles here: https://github.com/slim-ai/engineering

Email me at [email protected] if you'd like to learn more.

If instead you have a cohort on hand — -i.e., you do not want to send your data to a third party for any reason, or perhaps you have energetic undergrads — -then you could alternatively consider local, open-source annotation such as CVAT and Label Studio. Finally, nowadays, you might instead work with Large Multimodal Models to have them annotate your data; more on this awkward angle later.

14. LabelStudio by Human Signal | Github | tutorial

For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.

Huh?

I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.

My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.

Pytorch is open source, Huggingface is open source. CUDA isn't. This is

https://labelstud.io/

and for annotating text spans there are so many open source tools

https://github.com/doccano/doccano

I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.

LabelStudio is free for single use. https://labelstud.io/

LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.

Label Studio is an open source data labeling tool that includes annotation functionality. It provides a simple user interface (UI) that lets you label various data types, including text, audio, time series data, videos, and images, and export the information to various model formats.