Engineering Manager, Ranking Platform

The Ranking Platform team builds and runs the services that coordinate contextualized and personalized ranking on Reddit. We build infrastructure, including a scatter-gather ranking coordination service, feature indexes, and scalable data pipelines that power personalized feeds, search, and other Reddit products. We partner closely with machine learning engineers who develop and productionize models, and with ML Platform teams that build inference and training services and feature stores.

Our team mantra is “Intention over Attention.” We help users fulfill their intention for visiting Reddit by connecting them with relevant content and communities. We are a team of builders who value impact, personal growth, openness, and kindness.

How You’ll Have Impact

As Engineering Manager for Ranking Platform, you will lead the team building a robust, scalable, reliable, and performant ranking and indexing platform. You will partner with senior engineers, backend architects, product managers, and ML leaders to translate product needs into a clear platform strategy and deliver it from ideation through production.

You will be accountable for the team’s health, growth, execution, and operational excellence. Working with technical leaders, you will guide architecture and investment decisions, improve the experience of teams building on the platform, and balance new capabilities with reliability, latency, and infrastructure cost.

What You’ll Do

• Lead: Set the team’s direction and roadmap with senior engineers and partner teams. Select, scope, and deliver high-impact initiatives that evolve the ranking coordination services, ML indexes, and data pipelines supporting Reddit’s feeds and discovery experiences.
• Build: Hire, onboard, and develop a high-performing engineering team. Set clear expectations, provide actionable feedback, manage performance, and create growth opportunities for engineers at different career stages. Maintain direct feedback loops with engineers using the platform, and use their feedback and adoption patterns to guide investment.
• Amplify: Coach engineers and technical leaders, delegate meaningful ownership, and build a culture of technical excellence, inclusion, and knowledge sharing. Protect engineers’ focus time by removing blockers, reducing unnecessary interruptions and keeping processes lightweight.
• Deliver: Turn multi-quarter platform investments into achievable milestones. Manage dependencies and risks, communicate tradeoffs and progress, and adapt priorities as partner and business needs evolve.
• Operate: Drive operational excellence through incident response, blameless postmortems, observability, safe rollouts, and proactive system hardening. Establish clear reliability and performance goals and use them to guide investment. Plan realistically for on-call work and unexpected requests, make reprioritization explicit and address unsustainable operational load.
• Collaborate: Build strong partnerships with Feed, Search, Ads, ML Platform, and infrastructure teams. Align roadmaps, resolve competing requirements, and make platform capabilities easier to adopt and operate.
• Evolve: Guide architectural improvements and engineering best practices that make ranking systems more efficient, maintainable, and scalable. Create space for experimentation and continuous learning while holding a high bar for production readiness, spotting unnecessary complexity and recognizing where simplification or consolidation would improve maintainability and help teams work more effectively.

What We’re Looking For

• • 5+ years of people management experience leading high-performing engineering teams, including hiring, coaching, career development, and performance management.
  • 7+ years of experience building large-scale backend distributed systems, including substantial experience developing and shipping production software.
  • Experience leading teams or major initiatives in ML infrastructure, recommendation or ranking systems, indexing, or streaming and batch data pipelines.
  • Strong technical judgment in high-throughput platform services and APIs, with the ability to guide tradeoffs among reliability, latency, scalability, data freshness, and cost alongside senior engineers.
  • A track record of defining technical direction and delivering platform initiatives across multiple quarters and teams, with clear prioritization and measurable outcomes.
  • Experience improving production operations through deployment automation, monitoring, system diagnosis, incident management, and reliability engineering.
  • High empathy, excellent organizational and communication skills, and the ability to build consensus across engineering and product teams. You can explain complex technical decisions to technical and non-technical audiences and lead effectively in a distributed environment.
  • Experience with Go or Python; Kubernetes, Docker, AWS, or GCP; data systems such as Redis, Postgres, Memcached, Solr, or Milvus; and streaming frameworks such as Apache Beam or Flink is a plus.
  • BS degree in Computer Science, a similar technical field, or equivalent practical experience.