Full-Time

Senior Staff Machine Learning Engineer

Confirmed live in the last 24 hours

Nextdoor

Nextdoor

501-1,000 employees

Connects users with nearby communities and services


Senior, Expert

San Francisco, CA, USA

Required Skills
Data Science
Natural Language Processing (NLP)
Requirements
  • B.S. in Computer Science, Applied Math, Statistics, Computational Biology or a related field
  • 7+ years of industry/academic experience of applying machine learning at scale
  • Experience leading complex ML projects
  • Experience collaborating with engineering, product and data science teams
  • Experience building ML models for consumer facing products
  • Proven engineering skills, with experience of writing and maintaining high-quality production code
  • Ability to work with and analyze large amounts of data
  • Ability to succeed in a dynamic startup environment
  • Experience with recommendation systems, deep learning models, feed/notification relevance, knowledge graph, Ads or NLP will be a big plus
  • Experience mentoring junior engineers and planning roadmaps
Responsibilities
  • Collect and gather datasets to build machine learning (ML) models that make real-time decisions for the Nextdoor platform
  • Analyze datasets and use important features to build low-latency models for decisions that need to be made quickly
  • Deploy ML models into production environments and integrate them into the product
  • Run and analyze live user-facing experiments to iterate on model quality by measuring impact on business metrics
  • Collaborate with other engineers and data scientists to create optimal experiences on the platform
  • Participate in in-person Nextdoor events, trainings, off-sites, volunteer days, and other team building exercises
  • Build in-person relationships with team members and contribute to the KIND culture that Nextdoor values

Nextdoor's platform is dedicated to enhancing real-world connections by enabling users to interact with neighbors, local businesses, and public services through an easily accessible online portal. This focus on fostering community bonds and supporting local ecosystems makes it a compelling place to work for those passionate about meaningful social interaction and community service. The company's reach, spanning over 315,000 neighborhoods in 11 countries, underscores its leadership in leveraging location-based technology for community engagement.

Company Stage

IPO

Total Funding

$1.3B

Headquarters

San Francisco, California

Founded

2011

Growth & Insights
Headcount

6 month growth

-7%

1 year growth

-6%

2 year growth

6%