Machine Learning Engineer | Personalization

Creata il 31-05-2019

Location Palo Alto

POSIZIONE CHIUSA Candidati ora

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Descrizione

About Houzz

Houzz is the leading home renovation and design platform in the world. We have a highly engaged community of more than 40 million unique monthly users who leverage our technologies to find inspiration for their next home project, connect with over 2.3 million home design and remodeling professionals and discover products in the Houzz Shop.

About the Role

We are looking for a world-class machine learning engineer to join our early stage team. Our team of machine learning engineers apply state-of-the-art algorithms to drive user engagement.

Our mission is to understand users, deliver the right content to the right people in the right format and drive user experience and monetization.

What You'll Do

Play a central role in improving ranking and recommendation to increase user engagement

Explore, implement and productionize information retrieval, natural language processing, knowledge graph and machine learning algorithms across the Houzz experience, including homefeed, photo, story, discussion, email, push notification, user modeling, etc.

Design and set up A/B experiments to improve key metrics and get insights from our experiment-intensive development process

Work as part of a small, collaborative team with designers, front-end engineers and analysts, owning end-to-end data and quality development flow and bringing new ideas to reality

At a Minimum, We'd Like You to Have

A strong background in machine learning, information retrieval, ranking, recommendation system, NLP, knowledge graph and user modeling

A Ph.D., M.S. or B.S. in Computer Science or a related engineering disciplines

Proficiency in at least one of the primary languages (Java, Python, Go, C++)

Ideally, You'll Also Have

Extensive knowledge and experience with large-scale information retrieval, ranking, personal relevance, freshness and diversity of content

Experience with production machine learning systems at scale

Experience with A/B experiment design and analysis

2+ years of full-time relevant industry experience