Senior Engineering Manager, Shopping Ads
New
100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)Full-TimeManager
Salary292,500 - 409,500 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- Machine LearningMentoringSoftware EngineeringDistributed Systems
Requirements
- 8+ years of software engineering or ML engineering experience, including experience leading engineering teams
- Strong hands-on technical depth in ads ranking, retrieval, targeting, recommendation systems, engagement modeling, or ML-driven optimization systems
- Experience building and operating large-scale distributed systems or ML systems in production
- Proven ability to operate as a technical lead manager (TLM), driving architecture and execution while managing and developing engineers
- Experience partnering with Product, ML Platform, Ads Serving, Data Science, and cross-functional stakeholders to deliver complex initiatives
- Strong systems thinking with the ability to balance technical quality, execution speed, scalability, and operational reliability
- Excellent debugging, prioritization, and execution skills in fast-moving production environments
- Strong communication and leadership skills with the ability to align teams around technical strategy and business priorities
Responsibilities
- Lead a high-performing team of software and machine learning engineers focused on Shopping Ads targeting, retrieval, ranking, and engagement models
- Drive technical execution for Dynamic Product Ads and Product Listing Ads across ads targeting, candidate retrieval, ranking integrations, model features, and engagement optimization
- Act as a hands-on technical leader by contributing to architecture reviews, technical design, debugging complex production issues, and guiding implementation decisions
- Partner closely with ML Platform, Ads Serving, Product, Data Science, Measurement, and Infrastructure teams to define roadmaps and deliver advertiser impact
- Improve scalability, latency, reliability, relevance, experimentation quality, and operational excellence across Shopping Ads systems
- Drive simplification and platformization efforts that improve developer velocity and reduce operational complexity
- Establish strong engineering practices around system design, experimentation, code quality, observability, and production ownership
- Mentor and develop engineers and technical leads while fostering a culture of technical rigor, accountability, speed, and pragmatic execution
- Identify architectural bottlenecks, technical debt, and scaling risks, and proactively drive solutions across organizational boundaries
- Stay current with industry trends in commerce advertising, recommendation systems, retrieval and ranking architectures, and Shopping Ads optimization
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