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Machine Learning Engineer - New Grad 2025

San Francisco, California, United States

#TeamNextdoor

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 315,000 neighborhoods across 11 countries.

Meet your Future Neighbors

At Nextdoor, Machine learning is transforming our product through personalization, and driving major impact across different parts of our platform including newsfeed, notifications, ads relevance, connections, search, and trust. 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 machine learning engineers who believe in the power of the local community to empower our members to make their communities great places to live.

Our New Grad positions are based in our offices in San Francisco or New York City. We offer a hybrid work environment, with the expectation to work in office six times per month. Learn more about the experiences of our new grads here.  

The Impact You’ll Make

You will be part of an avid 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. 

  • Build and iterate on ML-driven products to foster creativity, discovery and engagement on Nextdoor.
  • Build personalized content and user recommendation systems used by millions of users every day.
  • Run and analyze live user-facing experiments to iterate on model quality
  • Collaborate with other engineers and data scientists to create optimal experiences on the platform

We have MLE positions across multiple tracks including Feed, Notifications, Ads, Network Growth, Knowledge Graph and ML Platform.

What You’ll Bring To The Team

  • Master’s Degree or Ph.D. in Computer Science, Applied Math, Statistics, or a related field; expected graduation between 2024 and Summer 2025
  • Deep understanding of machine learning concepts (e.g. deep learning) and applications (e.g. recommender systems, knowledge graph)
  • Internship in machine learning engineering in a related field (e.g. social networking, e-commerce)
  • Strong programming skills in Python or Java
  • Effective communication and collaboration skills
  • Passion for the Nextdoor’s mission and purpose
  • Bonus Points - Industry experience of applying machine learning at scale 

Rewards

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 $150,000 to $170,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. 

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.

Benefits

We’ve got you covered! We are dedicated to supporting your personal and professional growth with a comprehensive benefits package that includes:

  • A variety of health plans, and a OneMedical membership for concierge care
  • Flexible paid time off
  • Dedicated volunteer days
  • Monthly wellness stipend
  • Mental health support
  • Gender affirming care
  • Stocked micro-kitchens and lunches at our offices

Applications for this position will be accepted until September 30, 2024

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.

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