- Company Name
- Nextdoor
- Job Title
- Machine Learning Engineer - Product
- Job Description
-
**Job title**: Machine Learning Engineer – Product
**Role Summary**:
Build, deploy, and iterate machine‑learning models that power real‑time personalization and relevance across the Nextdoor platform. Work closely with product, data science, and engineering teams to produce low‑latency models for newsfeed, notifications, ads, and search, delivering measurable business impact through A/B experiments and analytics.
**Expactations**:
- Deliver fully functional ML solutions that meet strict latency and accuracy targets.
- Publish well‑documented, production‑grade code and maintain reproducible pipelines.
- Quantitatively assess model performance against business metrics and iterate quickly.
- Communicate insights and recommendations to product owners and stakeholders.
**Key Responsibilities**:
- Collect and curate large, heterogeneous datasets for model training and evaluation.
- Engineer features and build recommendation, ranking, or NLP models at scale (e.g., feed relevance, ads, knowledge graphs).
- Deploy models into production environments, integrating them into the user‑facing product.
- Run live, user‑facing experiments; analyze results and refine models.
- Collaborate with engineers, data scientists, and product managers to define requirements and success criteria.
- Establish reusable ML engineering patterns and best practices for future teams.
**Required Skills**:
- 1+ years of industry experience building ML models for consumer‑facing products.
- Strong proficiency in Python, PyTorch/TensorFlow or similar frameworks.
- Experience with recommendation systems, ranking algorithms, deep learning, or NLP at scale.
- Familiarity with data engineering (SQL, Spark, BigQuery, or similar) and model serving (ONNX, TensorFlow Serving, etc.).
- Proven ability to write clean, maintainable, production‑grade code.
- Excellent analytical skills: working with large datasets, feature engineering, experimentation.
- Adaptability to a fast‑moving, startup‑style environment.
- Passion for applying AI responsibly to enhance user well‑being.
**Required Education & Certifications**:
- Bachelor’s degree in Computer Science, Applied Mathematics, Statistics, Computational Biology, or a closely related field.
- Certifications in data science or ML (e.g., AWS Certified Machine Learning, GCP Professional AI Engineer) are a plus but not mandatory.
San francisco, United states
Hybrid
Fresher
04-01-2026