Machine Learning Engineer - New Grad 2026

About Nextdoor

Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale.

About the Role

Machine Learning is one of the most critical teams at Nextdoor. ML is transforming the product through personalization, driving significant impact across various platform components, including newsfeed, notifications, ad relevance, connections, search, and trust. The machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange.

At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we're looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs.

We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience. Offices are located in San Francisco, Los Angeles, Chicago, Dallas, New York, and London.

Responsibilities

• Build and iterate on ML-driven products to foster creativity, discovery, and engagement on Nextdoor
• Develop personalized content and user recommendation systems that millions of users rely on daily
• 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
• Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises
• Build in-person relationships with team members and contribute to Nextdoor's company culture

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

Requirements

• Education: Master's Degree or Ph.D. in Computer Science, Applied Math, Statistics, or a related field, graduating in December 2025/May-June 2026
• Machine Learning expertise: Deep understanding of machine learning concepts (e.g. deep learning) and applications (e.g. recommender systems, knowledge graph)
• Experience: Internship in machine learning engineering in a related field (e.g. social networking, e-commerce)
• Programming: Strong programming skills in Python or Java
• Soft skills: Effective communication and collaboration skills
• Mission alignment: Passion for Nextdoor's mission and purpose

Bonus points: Industry experience of applying machine learning at scale

Compensation & Benefits

Salary: The starting salary for this role is expected to be $150,000 to $175,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. The salary range will be determined by the candidate's geographic location.

Equity: We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date.

Perks & Benefits:

• Access to benefits (including mental health benefits, commuter benefits, wellness benefits, gender affirming care, etc)
• Flexible paid time off
• Dedicated volunteer days
• Stocked micro-kitchens and lunches at our offices
• Ability to join any of our Employee Resource Groups (ERGs)

Diversity & Inclusion

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 serve. We encourage everyone interested in our mission 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.