Reddit - Engineering Manager, Ads ML Efficiency
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. • Hands-on Optimization Background: • Strong Managerial Ability: Experience building and leading teams, coaching engineers, managing delivery, and making prioritization tradeoffs under ambiguity. • Strong Managerial Ability: • Distributed Systems Fluency: Proven ability to reason about production-scale ML systems and the tradeoffs that govern reliability, speed, cost, and scale. • Distributed Systems Fluency: • 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. • Customer and Platform Instincts: • Strong Communication: Can explain technical tradeoffs clearly to engineers, PMs, and senior stakeholders. • Strong Communication: • Ads experience: Experience in ads ranking, recommender systems, marketplace ML, or adjacent production ML domains is strongly preferred. • Nice-to-have: • Experience with GPU training and serving migrations. • Experience with PyTorch, distributed training frameworks, or kernel/performance optimization. • Experience building efficiency benchmarking or launch certification frameworks. • Experience working in organizations where ML platform and applied modeling responsibilities are split across multiple teams.
Responsibilities
• Lead & Grow: Hire, mentor, and retain a high-performing team of ML engineers / systems-oriented engineers working on model optimization and ML efficiency. • Lead & Grow: • Set Technical Direction: Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML. • Set Technical Direction: • Deliver Measurable Wins: Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk. • Deliver Measurable Wins: • Build Systems and Tooling: Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems. • Build Systems and Tooling: • Operate in the Critical Path: Partner with model owners and platform teams to accelerate high-priority launches and remove bottlenecks from the path to production. • Operate in the Critical Path: • Shape the Team’s Evolution: Balance near-term white-glove optimization work with medium-term platformization and automation. • Shape the Team’s Evolution: • Build XFN Alignment: Work closely with MLP, AMP, Ranking, and serving teams to clarify boundaries, upstream generic wins, and keep Ads needs on track. • Build XFN Alignment: • Raise the Bar: Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work. • Raise the Bar:
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 • Pay Transparency: • Pay Transparency: • This job posting may span more than one career level. • In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. • To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. • The base salary range for this position is: • $230,000—$322,000 USD • In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. • During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
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