Machine Learning Engineer - Data Monetization (Multiple Positions & Levels)

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 a MLE on the Data Monetization team, you will primarily be focused on building the best systems to ingest partner data in a privacy-safe way, and getting the most out of the data to power the rest of our models and products.

This role involves a lot of collaboration with the Product org and working with customers directly in order to build private-by-design technology (embedding models where one party controls the code and the other controls the data, provably encrypted ways to share identifiers, etc.).

Significant "wearing your Product hat" is expected, along with driving results in the many domains required to deliver whole ML-powered products - we are a quickly growing startup after all!

What it takes to succeed in this role:

• Can think creatively about data - are there ways to extract signal from partially obfuscated sources?

• Knows when to use a Data Clean Room and when it's just a buzzword

• Understanding enough about machine learning to be dangerous but not necessarily published in field

  • Worked on and can speak to some kinds of impactful consumer-facing ML problem, e.g. recommender systems, personalization, etc. 

• Skill and attitude wise, can quickly contribute to things such as orchestration/Airflow, Bazel (build systems, really), CI/CD, Spark (we have both Python and Scala), and other SQL-y data computation backends as needed. Not everybody is going to be a rockstar on all of these, and we are making novel tech investments across the company, but successful engineers will see opportunity and a path to (first) PR, instead of "not my job".

• Good product sense, has 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.