On-demand webinar with Microsoft & Github: Git-Based CI / CD for Machine Learning & MLOps
At Iguazio, our dream is to enable anyone to create innovative AI that directly impacts our world. As serial entrepreneurs, our founders empower us every day to transform this vision into reality.
We’re not just building a platform. We’re uncovering brand new ways to solve the most complex problems across the business world. And to do that, we experiment with the most sophisticated, cutting edge technologies of our time.
We’re growth seekers. Challenges are not problems to us – they’re opportunities to learn new skills, broaden our experience, and refine our craft. And as we grow, Iguazio does too. Backed by $50 million in funding, our technological journey is only just beginning.
At Iguazio, you’re encouraged to speak up, share your opinion, and challenge the status quo. Because if you’re here, you’re an expert at something. And you’ll be treated that way.
As a Data Scientist @ Iguazio you will be part of our CTO innovation team and contribute to the development and delivery of our Machine learning automation solution.
You will be working with our cutting-edge technology while bringing into play your data science experience and scientific knowledge to help our enterprise customers bring their data science to life. You’ll be implementing data-science and feature engineering modules in variety fields (ML, DL, NLP, ..) for iguazio open-source ML automation framework (MLRun), you will solve complex problems, build demos and take part in major customer POC projects, helping enterprise customers utilize their data with Iguazio’s groundbreaking platform.
You can expect to:
The ideal candidate will have the following:
The Iguazio Data Science Platform enables you to develop, deploy and manage AI applications at scale, transforming AI projects into real-world business outcomes. With Iguazio, you can build and run AI applications in real-time, deploy them anywhere (multi-cloud, on-prem, edge), and bring to life your most ambitious data-driven strategies.