Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.
Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 305,000 neighborhoods across 11 countries.Meet Your Future Neighbors
The cross-functional Neighborhood Vitality product team focuses on the reduction of harmful and hurtful content, improving the quality of the content on the platform, promoting positive interactions between neighbors, and verification of neighbors and organization. As a community platform, we team believes that machine learning should be ethical and encourage healthy interaction. Each member of the team believes that technology can be used to empower communities and drive change offline.The Impact You’ll Make
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.Day-to-day Responsibilities Include
Within Vitality, we you will use machine learning to automatically understand, report, and action user-generated content, to power in-product interventions which can norm neighbors toward positive interactions (see this recent blog post for an example of that work), and to provide signals to surfaces such as Feed and Notifications to limit the distribution of abusive content on the platform.
What You’ll Bring To The Team
- 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
- B.S. in Computer Science, Applied Math, Statistics, or other quantitative field, or equivalent work experience
- 2+ years of industry experience of applying machine learning in production at scale
- Initiative and eagerness to work in a dynamic startup environment
- Master’s / Ph.D. in Computer Science, Applied Math, Statistics, or other quantitative field
- 4+ years of industry experience of applying machine learning at scale
- Experience with natural language processing techniques
- Experience of building ML models for large community or social platforms
- Experience of building ML models in the domain of trust & safety, or moderation
- Exposure to or interest in social science and psychology
- Python experience
Compensation, benefits, perks, and recognition programs at Nextdoor come together to create one overall rewards package.
The starting salary for this role is expected to range from $104,000 to $192,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. Compensation may also vary by geography.
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.
Overall, total compensation will vary depending on your relevant skills, experience, and qualifications.We have you covered! Nextdoor employees can choose between a variety of great health plans. We cover 100% of your personal monthly premium for health, dental, and vision – and provide a OneMedical membership for concierge care.
At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.