Yobi is a rapidly growing tech company in the behavioral modeling and personalization space. Our mission is to ethically democratize the AI revolution. Since our founding in 2019, we have been busy assembling one of the largest consented behavioral datasets in the US, beyond the walled gardens of BigTech. This diverse understanding of consumer intent underpins a proprietary, private-by-design AI model that supercharges machine learning and marketing performance for some of the worlds leading brands, agencies, and Martech / AdTech platforms.

At Yobi we believe that every employee should be empowered to own 0-1 contributions and have the opportunity to achieve real impact - and scale that impact - on the business. If that sounds like an exciting opportunity to you, we want to hear from you.

Yobi Highlights

• Partnerships with Microsoft and Databricks

• Fully remote or hybrid from several hubs (Boston, SF Bay Area, Seattle, NYC)

• World-class team of Machine Learning experts who worked on cutting edge recommender systems and internal tools @ Amazon, Uber, Twitter, Meta, etc.

• Product and Go-To-Market teams who have taken ideas from concept to 9 figure revenue streams

Benefits

• Competitive Base Salary

• Bonus structure for qualifying employees

• Meaningful equity & financial upside - a real % of the company

• Health, Dental, Vision

• Flexible PTO

• 401k

About The Role

As an MLE on the Core Signals team, you will primarily be focused on (1) the representation learning surrounding our fundamental user-behavioral modeling problems and (2) using those core models to power new and existing products.

This role involves a lot of collaboration with the Product org and Applications team to realize these R&D gains - but is ultimately a "full stack" ML role. Day to day responsibilities include data processing, model training, deployment, and evaluation.

A good amount of "wearing your Product hat" is expected, as well as ability to flex into some other functions as needed - we are a quickly growing startup after all.

• You understand enough about machine learning to be able to apply it to novel problems and suggest improvements to our current setup, or even radical new approaches. Previous publication experience is not required.

• You've worked on and can speak to at least some of: representation learning, embeddings drift, CTR modeling, sequence modeling, etc., preferably on "big data" in an industrial setting.

• Skill and attitude wise, you can quickly contribute to the non-research components of our pipeline. This includes things such as data orchestration, build systems, and experiment tracking. Although we use a combination of open source products like Airflow, Bazel, Github CI/CD, and Spark, prior experience with these specific solutions is not needed. However, a good part of your day to day will involve interacting with these systems, so you should be comfortable with getting your hands dirty.

• Good product sense - you have opinions on what we should and shouldn’t be doing both in chasing product-market fit and on the implementation side.

We prioritize attitude, culture, and general (technical) fit over matching perfectly into one of our job descriptions. If our mission and work resonates with you, we encourage you to apply. Tell us how you can help drive our products forward, even if you don’t feel like you are a perfect fit for some of the listings.