Machine Learning Engineer, Nextdoor

Infrastructure

$142-213k

+ equity with equal quarterly vesting, your first vest date would be within the first 3 months of your start date

SQL
AWS
Docker
Kubernetes
Python
Scala
Java
Kafka
Go
Tensorflow
Spark
PyTorch
Unix
Junior, Mid and Senior level
San Francisco Bay Area
Nextdoor

Private social network for neighbours

Job no longer available

Nextdoor

Private social network for neighbours

501-1000 employees

B2CPrivacyNetworkingSocialSaaS

Job no longer available

$142-213k

+ equity with equal quarterly vesting, your first vest date would be within the first 3 months of your start date

SQL
AWS
Docker
Kubernetes
Python
Scala
Java
Kafka
Go
Tensorflow
Spark
PyTorch
Unix
Junior, Mid and Senior 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

  • You should be comfortable with petabytes of data, writing crisp design documentation, and building, debugging, and maintaining highly available distributed systems
  • Bring a deep empathy for customer needs and insights as well as an intuitive grasp of the business problems we’re trying to solve
  • Extensive experience in one or more of the following languages: Python, Go, Java, or Scala
  • Experience in designing, building, and debugging distributed systems
  • Proven engineering skills. Experience of writing and maintaining high-quality production code
  • A strong ability to partner with other data engineers throughout the company, and consult, design, and review their projects
  • Strong collaboration and communication skills, both verbal and written
  • Ability to succeed in a dynamic startup environment

Desirable

  • Master / Ph.D. in Computer Science, Applied Math, Statistics, Engineering or a related field
  • 2+ years of industry experience of applying machine learning at scale
  • 2+ years of experience in building performant and scalable backend services
  • Experience with Python, Kubernetes, Go, Kafka, Docker, Spark, SQL, AWS and the Unix environment
  • Experience with machine learning libraries and frameworks like Xgboost, Sklearn, TensorFlow, PyTorch, etc

What the job involves

  • At Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform including our newsfeed, our notifications, and our ads relevance
  • Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange
  • We believe that ML will be an integral part of making Nextdoor valuable to our members
  • We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior
  • We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live
  • You will be part of a scrappy and impactful team building data-intensive products, working with data and features
  • You will help build the foundational Machine Learning (ML) infrastructure that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform
  • The Machine Learning platform that you build will empower developers throughout Nextdoor to build better ML products more quickly than ever before
  • You will design, implement and integrate the next generation of Machine Learning infrastructure to empower our Data Scientists and Machine Learning engineers to build machine learning (ML) models that make real-time decisions for the Nextdoor platform
  • You will collaborate with other engineers and data scientists to create optimal experiences on the Core ML platform, including but not limited to: the featurestore, the real-time serving layer and the offline training system

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

Salary benchmarks

We don't have enough data yet to provide salary benchmarks for this role.

Submit your salary to help other candidates with crowdsourced salary estimates.

Share this job

View 27 more jobs at Nextdoor