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ZipRecruiter

Staff Machine Learning Scientist

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  • +8
  • US
    United States
Manifester de l'intérêt pour ce poste
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  • +8
  • US
    United States

À propos

Job Description
Staff Machine Learning Scientist
Location:
SF Bay Area - Hybrid (3 days/week onsite)
Salary:
$275-325k base + Equity
A leading commerce marketplace with 130M+ users and billions of daily events is hiring a Staff Machine Learning Scientist to drive innovation across personalization, feed ranking, computer vision, and GenAI. You'll work on high-impact ML solutions that directly shape user experience and business outcomes at massive scale.
What You’ll Do
Lead full-lifecycle ML projects from idea to production across core areas like personalization, trust & safety, marketing optimization, and user engagement.
Own the ML development process—from data exploration and feature engineering to model training, deployment, and post-launch optimization.
Collaborate cross-functionally with ML engineers, PMs, and business stakeholders to identify and prioritize high-leverage initiatives.
Experiment with emerging AI techniques, including GenAI, Computer Vision, and LLMs, to push the boundaries of what’s possible on the platform.
Build scalable, production-ready ML systems that enhance key metrics like retention, engagement, and conversion.
What You Bring
7–10 years of experience building, deploying, and maintaining ML models at scale.
Deep expertise in Python, SQL, Spark (PySpark or Scala) and frameworks like PyTorch or TensorFlow.
Proven track record in consumer tech or large-scale marketplaces companies.
Hands-on experience with CNNs, Transformers, Vision Transformers, and personalization algorithms.
Background in user behavior modeling, search relevance, or real-time data systems.
Strong foundation in experimentation (A/B testing), statistics, and applied ML.
Exceptional communication skills and the ability to translate technical insights into business value.
Experience with LLMs, RAG (Retrieval-Augmented ), or PEFT (Parameter-Efficient Fine-Tuning) techniques.

Compétences idéales

  • Machine Learning
  • PySpark
  • PyTorch
  • Python
  • SQL
  • Scala
  • Spark
  • TensorFlow
  • United States

Expérience professionnelle

  • Machine Learning
  • Computer Vision
  • Search

Compétences linguistiques

  • English