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Engineering Manager, Ads ML Efficiency

Engineering ManagerEngineering ManagerFull TimeRemoteSeniorTeam 501-1,000Since 2005H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

3 days ago

Salary

$230K - $322K / year

Seniority

Senior

Bachelor DegreeEnglishDistributed Systems

Job Description

Engineering Manager, Ads ML Efficiency

Reddit, Inc.

• Hire, mentor, and retain a high-performing team of ML engineers/systems-oriented engineers working on model optimization and ML efficiency. • Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML. • Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk. • Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems. • Partner with model owners and platform teams to accelerate high-priority launches and remove bottlenecks from the path to production. • Balance near-term white-glove optimization work with medium-term platformization and automation. • Work closely with MLP, AMP, Ranking, and serving teams to clarify boundaries, upstream generic wins, and keep Ads needs on track. • Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work.

Job Requirements

  • Deep ML Engineering Experience: The candidate should have been close to the models themselves and understand training, serving, debugging, and optimization in depth.
  • Hands-on Optimization Background: Direct experience improving training loops, serving systems, profiling workflows, model/inference efficiency, or GPU utilization.
  • Strong Managerial Ability: Experience building and leading teams, coaching engineers, managing delivery, and making prioritization tradeoffs under ambiguity.
  • Distributed Systems Fluency: Proven ability to reason about production-scale ML systems and the tradeoffs that govern reliability, speed, cost, and scale.
  • Customer and Platform Instincts: Able to work as a service provider to modeling teams while still building reusable systems rather than only heroic one-offs.
  • Strong Communication: Can explain technical tradeoffs clearly to engineers, PMs, and senior stakeholders.
  • Ads experience: Experience in ads ranking, recommender systems, marketplace ML, or adjacent production ML domains is strongly preferred.

Benefits

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

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