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Staff Machine Learning Engineer

ZipRecruiter · Remote, Santa Monica, CA

remotesenior$205,000–$265,000Posted Sep 3, 2026PyTorchTensorFlowMachine LearningRecommendation SystemsNeural NetworksA/B TestingMLOpsPython

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About this role

**Staff Machine Learning Engineer** **Work Environment:** Hybrid role with remote options available for most US-based positions. **About ZipRecruiter:** Leading online employment marketplace powered by AI-driven smart matching technology, connecting millions of businesses and job seekers. #1 rated job search app on iOS & Android. **Role Summary:** We're seeking a Staff Machine Learning Engineer / Data Scientist to serve as a technical anchor for our ML and AI capabilities. You'll report directly to the Director of Recommendation Systems and shape our multi-year ML roadmap while translating complex research into high-throughput, low-latency production systems. **Key Responsibilities:** • Drive ML strategy and roadmap for core marketplace components including recommendation engines, matching algorithms, and ML entity representation • Architect high-scale systems handling dynamic interaction prediction, candidate ranking, and retrieval • Optimize two-sided marketplace dynamics including real-time intent prediction and bilateral relevancy • Provide org-wide technical leadership and mentorship to ML engineers across teams • Own end-to-end model lifecycle from exploration through production optimization **Minimum Qualifications:** • 8+ years developing and deploying ML models in large-scale production environments • Proven track record architecting and shipping end-to-end ML solutions at scale • Deep expertise in Recommendation Systems, Personalization, Ranking & Retrieval, or Interaction Prediction • Strong software engineering fundamentals with hands-on deep learning framework experience (PyTorch, TensorFlow) • Demonstrated technical leadership and mentorship experience • Strong background in statistical modeling, A/B testing, and metric design **Preferred Qualifications:** • Experience in two-sided marketplaces (supply/demand, bilateral matching, dynamic pricing) • Modern deep learning techniques (Two-Tower Networks, GNNs, Transformers, Contextual Bandits) • Advanced degree (MS/PhD) in CS, ML, or related quantitative field • Experience with MLOps architectures and distributed training frameworks **Compensation & Benefits:** • Salary: $205,000 - $265,000 USD • Competitive compensation and exceptional benefits • Flexible PTO • Employer-matched 401(k) • Equity, bonuses, and additional compensation may apply **Equal Opportunity Employer**

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