Senior/Staff Machine Learning Engineer, Nextdoor

Product

$190-355k

We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date

Python
Senior and Expert level
San Francisco Bay Area
Nextdoor

Private social network for neighbours

Open for applications

Nextdoor

Private social network for neighbours

501-1000 employees

B2CPrivacyNetworkingSocialSaaS

Open for applications

$190-355k

We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date

Python
Senior and Expert level
San Francisco Bay Area

501-1000 employees

B2CPrivacyNetworkingSocialSaaS

Company mission

Nextdoor’s mission is to cultivate a kinder world where everyone has a neighbourhood they can rely on.

Role

Who you are

  • B.S. in Computer Science, Applied Math, Statistics, Computational Biology or a related field
  • 5+ years of industry/academic experience of applying machine learning at scale
  • 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

What the job involves

  • You will be part of a scrappy and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will be working closely with the product team and the Data Science team on a daily basis. Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform
  • Collect and gather datasets to build machine learning (ML) models that make real-time decisions for the Nextdoor platform
  • Analyze datasets and 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

Our take

Nextdoor is a private social network that aims to encourage social interaction between neighbours and make people aware of crime in their area.

The social network has had huge success in the United States and has expanded internationally, with Nextdoor now present in more than 242,000 neighbourhoods around the world.

The company's main competition comes from local Facebook groups, which have become less and less popular due to their comparative lack of functionality. Nextdoor's laser focus on building for neighborhoods has helped them to build a better product, and their advertising partnership with Oracle, launched in 2022, will help bring more transparency to Nextdoor's sponsorships.

Steph headshot

Steph

Company Specialist

Insights

Top investors

Few candidates hear
back within 2 weeks

8% employee growth in 12 months

Company

Funding (2 rounds)

May 2019

$129.1m

Dec 2017

$78.8m

Total funding: $207.9m

Company benefits

  • Monthly wellness stipend
  • 12 weeks of parental, family or medical leave
  • Global end of year shutdown
  • Learning and development stipend
  • Work from home opportunities
  • Health insurance

Company values

  • Earn trust every day
  • Invest in community
  • Customer obsessed
  • Think big
  • Experiment and learn quickly
  • Act like an owner

Company HQ

SoMa, San Francisco, CA

Leadership

Prakash Janakiraman

(Advisor & Co-founder)

Graduated from the University of California, Berkeley before working in engineering roles at Google and as the co-founder of Fanbase.com

David Weisen

(Engineer & Co-founder)

Worked as a software engineer at Google, Fanbase.com and Open Harbour after graduating from Stanford with a degree in Computer Science

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