#TeamNextdoor

Nextdoor is the neighborhood hub for trusted connections and the exchange of helpful information, goods, and services.

Building connections in the real world is a universal human need. That truth, and the reality that neighborhoods are one of the most important and useful communities in our lives have been guiding principles for Nextdoor. Today, neighbors rely on Nextdoor in neighborhoods around the world in the United States, the United Kingdom, Germany, France, the Netherlands, Italy, Spain, Sweden, Denmark, Australia and Canada, with many more to come.

Meet your Future Neighbors

At Nextdoor, 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 local ecosystem. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We are scrappy and 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 local community to empower our members to make their communities great places to live.

The Impact You’ll Make

You will be part of a scrappy and impactful team building a scalable ML platform in a rapidly changing company. In this role, you will focus on developing the underlying data processing infrastructure to support the ML platform in collecting data, labeling data, and using data to monitor model performance. You will also build infrastructure to train, serve, and monitor ML models. Finally, you will be responsible for building platform-wide model features that the entire company can utilize in building ML models. As a result, you will be laying the foundation for a critical part of Nextdoor’s mission.

What You’ll Bring to The House

• B.S. in Computer Science, Math, Statistics, or a related field.
• 5+ years of industry/academic experience building infrastructure at scale.
• Proven engineering skills. Experience writing and maintaining high-quality production code. 
• Proficient in Python

Bonus Points

• Experience using AWS to build data-intensive infrastructure: ECS, Kinesis, S3, Flink
• Experience building platforms around publicly available ML platforms like Sagemaker, Kubeflow, MLflow, etc.
• Experience serving models using a variety of ML model frameworks like Tensorflow, PyTorch, Sci-kit Learn, etc.