Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Distributed Systems @ 4
Machine Learning @ 4
Data Science @ 4
Leadership @ 7
Communication @ 7
Mentoring @ 4
Prioritization @ 4
Debugging @ 4
Experimentation @ 4
Observability @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Reddit's Shopping Ads Engineering team builds the systems that power performant, relevant, and scalable Shopping Ads experiences across Reddit’s Ads platform, including Dynamic Product Ads (DPA) and Product Listing Ads (PLA). The team focuses on Shopping Ads targeting, retrieval, and engagement modeling to connect advertisers with high-intent users and improve downstream ads performance. This role is a hands-on Engineering Manager / Technical Lead Manager (TLM) responsible for driving technical execution, architecture, and mentoring while remaining deeply involved in system design and production problem solving.
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.
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.
- Familiarity with modern ads ecosystem trends, commerce advertising, and recommendation architectures is a plus.
Benefits
- 100% remote opportunity (offices available in New York City, San Francisco, Los Angeles, and Chicago for hybrid/onsite preference).
- Competitive salary and equity options.
- Comprehensive health benefits (medical, dental, vision) and workplace perks (home office setup stipend, etc.).
- Generous 401(k) matching.
- Flexible vacation policy.
- Paid parental leave (4+ months) and family planning support.
- Paid volunteer time off.
Pay Transparency
- Base salary range for this U.S.-based position: $292,500 - $409,500 USD.