Machine Learning at Crunchbase

At Crunchbase, we have Machine Learning Engineers in different teams including the Personalization team and the Graph team. Machine Learning engineers work on an array of challenges from creating features with personalized relevant information throughout the our users’ experience on Crunchbase to automatically understanding data and structuring it into our knowledge graph. The Data Science and Machine Learning guild is thriving to enable us to deploy Machine Learning algorithms with data from many different sources including our own platform, and user behavioral data, we learn our users’ journey and build a personalized experience that is unique to each user.

What You'll Do:

We are hiring a hands-on Staff Machine Learning Engineer. The ideal candidate is passionate about not only data and what it can teach us, but also about our users and how to drive an experience that helps them engage with and better utilize our data. 

Help drive the Machine Learning at Crunchbase to the next level. Develop and support Data Science modelling in production. Implement, deploy, test and evaluate the impact of services that drive features which impact our users experience. Help establish processes and best practices to help grow the Data Science and Machine Learning guild and contribute to defining and enhancing our machine learning platform capabilities from the ground up.

What We're Looking For:

• You have an advanced degree in a quantitative discipline and have strong Python foundations.
• You have 5+ years of proven industry experience.
• You hold a high bar on code quality and enjoy building systems and tools that can be used by others.
• You are an excellent communicator and able to explain complex issues to stakeholders in simple terms.
• You have hands-on experience in shipping machine learning-based projects in production.
• Experience working in production systems and enabling LLMs and other MLs models.
• Dealing with large amounts of data on a daily basis is a plus.
• You care about being agile, cross teams collaborations, and data-driven development and evaluation.
• You are a big believer in the Build-Measure-Learn methodology.