Engineering Team Lead - Machine Learning

Company: Nextdoor
Location: San Francisco, California, United States
Type: Full-time
Posted: 31.JUL.2021

Summary

#TeamNextdoor Nextdoor is where neighbors turn for trusted connections and the exchange of helpful information, goods, and services. Nextdo...

Description

#TeamNextdoor

Nextdoor is where neighbors turn for trusted connections and the exchange of helpful information, goods, and services. Nextdoor's purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.

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 and notifications. 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 a great engineering leader who believes in the power of the local community to empower our members to make their communities great places to live.

The Impact You'll Make

You will be leading 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. Some of the current products / projects you could work on include the newsfeed, navigation and search, notifications. You will build critical decision-making models for the product, enhancing the relevance and value of our products. 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.

  • Facilitating collaboration across a cross-functional team which includes product, design, engineering, machine learning, and data science
  • Leading and developing a prioritized roadmap for content ranking efforts which aligns with Nextdoor's goals
  • Ensuring project health and progress using project management tools such as Jira
  • Ensuring the quality and timeliness of shipped experiments and products
  • Providing technical guidance at the architecture, model, and product level as well as helping to execute on the projects with hands-on model-building and coding
  • Recruiting, building, coaching and mentoring engineers to reinforce engineering excellence
  • Promoting a culture of feedback and transparent communication
What You'll Bring to The Team
  • 1-3 years of experience leading technical aspects of a cross-functional engineering team which includes product, data science, and engineering.
  • 4-8+ years of relevant engineering experience working on the development of ML-based products at consumer-facing companies that make complex decisions and have an impact on users.
  • Experience collaborating with teams across an organization, prioritizing the work that is requested from external teams, and keeping the team focused on delivery with many pressing priorities
  • Experience being a collaborative, thoughtful and strategic leader, who is comfortable with open communication and giving/receiving constructive feedback respectfully.
Bonus Points
  • Successful track record of building ML products related to Recommendation Systems, Personalization, Search or Feed Ranking
  • Experience in specialized areas such as Deep Learning, Reinforcement Learning, Bandits, Natural Language Processing or Forecasting

 
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