Have you worked on real life, practical implementation of AI / ML projects? Are you interested in using AI / ML to disrupt how humans and teams work and collaborate? Then we're looking for you!
- We are building an information management system based on a fast text interface.
- Our goal is to make editing a complex information graph as simple as writing a text document.
- Our AI components will work interactively with users to enhance their text input to create a semantically tagged and interlinked data graph
- Potential areas for assistive AI are clustering, POS tagging, entity recognition, classification, summarization , de-duplication, auto-suggestions of content transformations and actions and more.
- We are a product startup, not an AI research lab.
- You are able to navigate the current state of tools and libraries to implement practical solutions, while keeping an eye on new research papers for future opportunities.
- You are motivated by being part of the product development team that aims to delight users with working features.
- As part of a close team covering Design, Product and Engineering
- Proof of concept explorations and prototypes that demonstrate what can be achieved with AI-based features as part of our UI & Product.
- Realization of production quality implementations of selected AI features based on open source or commercially available libraries, models and services
- Tracking the developing field of AI, with a focus on identifying realistic approaches and solutions related to the area that Tagr addresses
- Experience in applying machine learning techniques particularly within Natural Language Processing
- Strong analytical and problem-solving skills.
- Solid software engineering skills across multiple languages
- Deep understanding of ML techniques such as: Classification, clustering, deep learning, word embedding, language models.
- Proven ability to apply, debug, and develop machine learning models for real-world applications.
- An overview of tools such as TensorFlow, Pytorch, Keras, SparkML with deep mastery of at least one of the leading deep learning frameworks.
- You're open and honest with others and with yourself
- You're curious
- You're a life-long learner
- You get a thrill when you can dig in deep, but you impatiently get things done
- You care about understanding the challenges humans and teams face in everyday work
- You love building stuff