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Salary
≈ $74k – $175k per year (Estimated)
Location
In office (Toronto)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Jul 15, 2026. Pinterest scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Pinterest is a visual discovery and social platform where users save and share images and ideas, headquartered in San Francisco, California.

Join Pinterest as a Machine Learning Engineer in Core Engineering. You will build cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest. You will partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces, while gaining knowledge of how ML works in different areas. You will work in a high-impact environment with quick experimentation and product launches.

Missions

  • Construire des technologies de pointe en utilisant les dernières avancées en apprentissage profond et en apprentissage automatique pour personnaliser Pinterest.
  • Collaborer étroitement avec les équipes de Pinterest pour expérimenter et améliorer les modèles d'apprentissage automatique pour diverses surfaces de produits.
  • Utiliser des méthodes basées sur les données et tirer parti des propriétés uniques de nos données pour améliorer la récupération des candidats.

Profil recherché

- M.S. or PhD in Machine Learning or related areas

- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)

- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)

- Passion for applied ML and the Pinterest product

- Expertise in scalable realtime systems that process stream data

- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring

- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration

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