Hiring: Staff Machine Learning Engineer, Recommendations Company: ZipRecruiter Location: Santa Monica, CA Job Posted Time: 2026-09-10 01:12:10 Employment Type: Full-time / Hybrid Target Skills & Keywords : A/B Testing, Android, Deep Learning, MLOps, Machine Learning, PyTorch, TensorFlow, TestNG, iOS About the job Experience: •8+ years of professional experience developing and deploying machine learning models in large-scale production environments. Required Skills: •Reporting directly to the Director of Recommendation Systems, you will be a core partner in shaping our multi-year ML roadmap, driving foundational algorithmic architecture, and translating complex machine learning research into high-throughput, low-latency production systems. •Beyond delivering core algorithmic gains, you will mentor Machine Learning Engineers across the organization and establish best practices for how ML models are built, deployed, and evaluated at scale. Qualifications: •8+ years of professional experience developing and deploying machine learning models in large-scale production environments. •Demonstrated success in 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. •Proven hands-on 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. •Practical experience utilizing modern MLOps architectures and distributed training frameworks. Compensation: •Flexible Vacation & Paid Time Off Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!