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:
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Partnerships with Microsoft and Databricks
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Fully remote or hybrid from several hubs (Boston, SF Bay Area, Seattle, NYC)
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World-class team of Machine Learning experts who worked on cutting edge recommender systems and internal tools @ Amazon, Uber, Twitter, Meta, etc.
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Product and Go-To-Market teams who have taken ideas from concept to 9 figure revenue streams
Benefits:
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Competitive Base Salary
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Bonus structure for qualifying employees
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Meaningful equity & financial upside - a real % of the company
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Health, Dental, Vision
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Flexible PTO
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401k
About The Role
At Yobi, Applications teams bring the value in our User-Behavioral foundation models to market, creating scalable, highly profitable products with ML at their heart. These Applications products are key to Yobi success, as they ground the value of our R&D, power continuous experimentation and improvement, and provide significant data for improving our core embeddings.
As an MLE on this team, you will primarily be focused on the models, metrics, pipelines, systems, and services that power and deliver excellence via Yobi Applications products.
This role involves a large degree of 0-to-1 development, and will rely on collaboration with Product, core signals MLEs, and leaning on your own expertise and insight in building holistic ML-powered products. While we currently have a product in the market here, we invite big bets to expand impact and reach.
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:
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AdTech experience and product intuition for the space
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Understanding enough about machine learning to be dangerous but not necessarily published in field
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Worked on and can speak to some kinds of impactful consumer-facing ML problem, e.g. recommender systems, personalization, etc.
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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".
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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.
Top Skills
What We Do
Since Yobi’s founding in 2019, we’ve been focused on solving the single biggest challenge to democratized AI for organizations of all sizes: ACCESS TO DATA.
Today’s Large Language Model’s lack a defensible moat because they’re trained on public data, like Reddit, WordPress, and other public web sites. Unfortunately, unless you’re Google or Amazon, your 1P data estate doesn’t provide a holistic consumer view to deliver real impact.
Yobi partnered with Microsoft to assemble one of the largest consented behavioral datasets to underpin a private foundation model of behavioral intelligence without sacrificing consumer choice or privacy.
For data scientists, this foundation model can be fine-tuned and joined to customer 1P data to ignite model training and performance.
For marketers, this big-tech like behavioral model can be plugged into open web activation and personalization platforms to unlock new levels of audience targeting and consumer experiences beyond the walled gardens.
Together, through collaboration, WE CAN DEMOCRATIZE THE AI REVOLUTION.