Facebook Software Engineer, Content Search Relevance in Seattle, Washington

Intro:

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.

Summary:

Facebook is seeking Machine Learning Engineers to join our Content Search & Relevance engineering team. This team builds a general purpose content search engine for Facebook. Given a keyword search query, we aim to rank the best links, photos, videos and posts for our diverse and rich query stream. We receive more than 200M content search queries/day, as part of >2B total search queries/day. Across all search verticals, a key building block is the ability to assess textual/semantic relevance of content to a user search query. This team is responsible for the relevance submodel and is measured on the quality of our ranking infra and the fraction of results that are relevant. The ideal candidate will have industry experience working on a range of classification problems, ranking, regression, clustering, natural language processing (query understanding, document understanding), information retrieval, supervised machine learning, and deep learning.

Required Skills:

  1. Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models

  2. Suggest, collect and synthesize requirements and create effective feature roadmap

  3. Code deliverables in tandem with the engineering team

  4. Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Minimum Qualifications:

  1. MS degree in Computer Science or related quantitative field or Ph.D degree in Computer Science or related quantitative field

  2. 5+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or artificial intelligence

  3. Proven ability to translate insights into business recommendations

  4. Experience with Hadoop/Hbase/Pig or MapReduce/Sawzall/Bigtable

  5. Knowledge developing and debugging in C/C++ and Java

  6. Experience with scripting languages such as Perl, Python, PHP, and shell scripts

Preferred Qualifications:

  1. Experience with filesystems, server architectures, and distributed systems

Industry: Internet

Equal Opportunity: As part of our dedication to the diversity of our workforce, Facebook is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at accommodations-ext@fb.com or you may call us at 1+650-308-7837.