monday.com
  • 101 active jobs (view)

  • Published: June 4, 2023
Category
Job Type
Level of education
Undergraduate
Spoken Language needed
Hebrew
Level of Hebrew
Fluent
Location of job
Tel Aviv/ Ramat Gan
How many relevant years experience do you require for the role:
More than 3 years

Description

monday.com is a Work OS that lets organizations manage all their work in one place. And like our platform, we are committed to building an organization with one shared mission.

We believe that the most effective teams are built on skills and passion, which is why in our recruitment process, in addition to learning about your background and experience, we really want to understand who you are and what empowers you.

monday.com is looking for a full-stack data scientist to join our brand new AI R&D team within the platform. You will take part in implementing generative AI capabilities within monday.com AI platform including defining the strategy of using LLMs, training it with proprietary data, and productizing it as part of our platform offering.

The ideal candidate will have a full-stack mindset, meaning they will actively participate in both the data-science, engineering, product, and business aspects of the role. You'll be utilizing the latest genAI technology to deliver maximum value and impact to our users.

monday AI team is responsible for the end-to-end generative AI features within the monday.com platform, creating new experiences and value for our users, and building the next-generation capabilities to enhance our platform. We invite you to join our exciting journey in pushing the boundaries of AI technology.

More about MondayAI-

About The Role:

- You will utilize cutting-edge generative AI technology to develop and deploy innovative features at scale within monday.com's ecosystem.
- You will be responsible for initiating, planning, designing, and executing AI flows from research to production.
- You will use your engineering background, deep understanding of AI models and data science methodologies to evaluate and develop AI-based pipelines.
- You will work closely with full-stack developers, product managers, data analysts, product designers and other stakeholders within the team to build production-ready capabilities for more than 2M users.

Social Title:

Full Stack Data Scientist - R&D AI Team

Social Description:

monday.com is looking for a full-stack data scientist to join our brand new AI R&D team within the platform. You will take part in implementing generative AI capabilities within monday.com AI platform including defining the strategy of using LLMs, training it with proprietary data, and productizing it as part of our platform offering.

Monday AI team is responsible for the end-to-end capabilities of generative AI within monday.com platform, creating new capabilities and values for our users and building it in the open platform way, so every 3rd party monday.com developer would be able to use it for building their AI applications.

REQUIREMENTS

- B.Sc. and ideally an advanced degree in a technical field such as Computer Science, Mathematics, Statistics, or equivalent experience
- 3+ years of experience as a Data Scientist in non-academic settings, ideally with a focus on Large Language Models, NLP or other deep learning fields
- A demonstrated record of conceiving, designing, and shipping successful data science projects to production
- Hands-on proficiency with modern generative AI models, prompt engineering, multi-agents, and RAG architectures. Also, a solid understanding of transformers, optimized fine-tuning techniques, and evaluation methodologies of LLMs while using relevant frameworks (Hugging Face, LangChain, LlamaIndex, etc)
- Strong understanding of machine learning and deep learning algorithms and principles and familiarity with relevant frameworks (TensorFlow, PyTorch, etc. )
- High proficiency in Python - A must
- Previous knowledge in Typescript - An advantage
- Team player with strong communication skills
- This is a full-stack role - an ideal candidate will not only be comfortable with algorithmic tasks and modeling but also have the technical know-how to set up and operate the environments and tooling that they require

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