Job Directory Machine Learning Engineer

Machine Learning Engineer
San Francisco, CA

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Job Description

About Wilbur Labs

Wilbur Labs is a startup studio building a portfolio of companies at the intersection of marketing and technology. We are founded by a team of ex-Googlers who are reinventing the way companies are built by leveraging data and automation across the entire business life cycle. This approach eliminates inefficiencies and opens the door to scaling much faster than traditional companies.

About This Role

We're looking for machine learning engineers to help with classification and optimization across our portfolio. You will apply your experience towards click-through rate prediction, search ranking, text/sentiment classification, and product recommendation engines.

We offer competitive salaries with top notch benefits and perks.

Role & Responsibilities:

* Build and deploy end-to-end machine learning models across multiple portfolio companies
* Design data driven products and systems with built-in feedback loops for self-optimization

Minimum Qualifications:

* Degree in CS or related quantitative field
* 5+ years of experience working with machine learning, pattern recognition, recommendation systems, or artificial intelligence
* Strong interpersonal communication and collaboration skills
* Self-starter who will thrive in an ambiguous startup environment
* Must be located in or willing to relocate to the San Francisco Bay Area

Preferred Qualifications & Prior Experience:

* Ph.D. degree in Computer Science or related quantitative field
* Experience using GCP and TensorFlow


* Competitive salary + equity
* 100% company paid health benefits
* 401(k) with company match
* Unlimited, guilt-free vacation days
* Uber/Lyft to and from work (employees based in San Francisco)
* Transportation stipend (employees based outside of San Francisco)
* Healthy breakfast, snacks and lunch provided daily
* Annual wellness benefit (gym + other wellness activities)
* Monthly house cleaning
* Annual travel allowance
* Quarterly team offsites
* State of the art ergonomics and work stations

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