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Staff Machine Learning Engineer, Recommendations

ZipRecruiter
Location
Remote, Santa Monica, CA
Posted
17 days ago
Department
710 Tech
Salary
$205,000.00-$265,000.00
What they actually want (must-haves)
  • 8+ years of professional experience developing and deploying machine learning models in large-scale production environments
  • Proven track record of architecting and shipping end-to-end ML solutions that serve production traffic at scale
  • Deep domain expertise in Recommendation Systems, Personalization, Ranking & Retrieval, or Interaction Prediction
  • Strong software engineering fundamentals with hands-on expertise using modern deep learning frameworks (PyTorch, TensorFlow)
  • Proven experience in technical leadership and mentorship, driving technical alignment across cross-functional engineering and product teams
  • Strong background in statistical modeling, online experimentation (A/B testing methodology), and offline metric design
Nice to have
  • Experience in Two-Sided Marketplaces: Familiarity with supply/demand liquidity, bilateral matching algorithms, dynamic pricing, or auction-based models
  • Modern deep learning techniques for recommendations, such as Two-Tower Neural Networks, Graph Neural Networks (GNNs), Transformer-based retrieval models, or Contextual Bandits
  • Advanced degree (MS/PhD) in Computer Science, Machine Learning or a related quantitative field or equivalent experience
  • Experience with modern MLOps architectures and distributed training frameworks
What the job really is

As a Staff Machine Learning Engineer at ZipRecruiter, you will be responsible for shaping the machine learning strategy and roadmap, particularly focusing on recommendation systems and matching algorithms. Your role involves architecting high-scale ML systems, mentoring other engineers, and driving the end-to-end model ownership process. You will tackle complex challenges in a two-sided marketplace environment, ensuring the delivery of high-performance, production-ready solutions.

Benefits
  • Competitive compensation
  • Exceptional benefits package
  • Flexible Vacation & Paid Time Off
  • Employer-matched 401(k) plan
Things to weigh
  • Remote work flexibility is available, but specific exceptions may apply
  • Salary range is provided, but individual pay is determined by various factors including location and experience
  • The role involves high visibility and technical leadership, which may come with significant expectations
Job score4.2/5
Benefits2/5
Freshness4/5
Career value5/5
Role clarity5/5
Pay transparency5/5

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