Machine Learning Engineer - Applied / Product

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!

Machine Learning, Artificial Intelligence (AI), Data Sets, Privacy Controls, Customer Acquisition, Sales Closing Skills, Web TV, Data Modeling, Large-Scale Systems, Machine Learning, * Understanding enough about machine learning to be dangerous but not necessarily published in the field. This means you have worked on and can speak to impactful consumer-facing ML problems, e.g. recommender systems, personalization, etc. that you have directly contributed to.

• Skill and attitude wise, you can quickly contribute to the “full stack” 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, has opinions on what we should and shouldn’t be doing both in chasing product-market fit and on the implementation side.

• Competitive Base Salary
• Meaningful equity & financial upside - a real % of the company
• Annual bonus target based on personal and company performance
• Health, Dental, Vision available
• Unlimited PTO - we care about impact, not tracking days you’re out
• 401k with company match %
• Generous parental leave policy, A reasonable estimate of the current base salary range at the time of posting is below. Base salary does not include other forms of compensation or benefits. Actual base salary within the specified range is comprised of several components, including but not limited to applicant’s skill, prior relevant experience, specific degrees and certifications, job responsibilities, market considerations and the location of the position.

Base salary range: $180,000-$275,000

Yobi is a rapidly growing Behavioral AI company on a mission to ethically democratize the benefits of data and AI.

Since 2019, we have built one of the largest consented behavioral datasets in the United States, extending far beyond the walled gardens of Big Tech. Unlike traditional LLM companies, Yobi builds foundation models of human behavior grounded in real-world actions such as purchases and store visits.

Our private-by-design modeling enables state-of-the-art personalization and decisioning for leading brands and agencies while protecting privacy, safety, and ethics.

Today, we are focused on bringing the performance of closed-web user acquisition to the open web and connected TV, giving brands walled-garden results without the walls.

At our core, Yobi is building the behavioral intelligence layer for any system that makes a personalization decision.

Working at Yobi

We’re at an inflection point-customer adoption is accelerating, but there’s still room to shape the architecture and culture from the ground up. Engineers here own major surface areas, build 01 systems in large-scale data and model infrastructure, and help define how Behavioral AI scales ethically and effectively.

Highlights:

• Partnerships with Microsoft and Databricks
• Fully remote or hybrid from several hubs (SF Bay Area, Seattle, NYC)
• World-class team of Machine Learning experts who worked on cutting edge infra and recommender systems @ Amazon, Uber, Twitter, Meta, etc.
• Product and Go-To-Market teams who have taken ideas from concept to 9 figure revenue streams