1 month ago

Engineering Manager, Ads ML Efficiency

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Lead a team focused on ML model optimization, training/inference efficiency, GPU enablement, and tooling to accelerate ads ML across training, serving, and launch-readiness. Drive measurable wins in training time, latency, and cost while partnering with ML Platform, Ranking, and serving teams to remove bottlenecks and scale efficiency across Ads ML.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Lead & Grow: Hire, mentor, and retain a high-performing team of ML engineers / systems engineers focused on model optimization and ML efficiency.
•Set Technical Direction: Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML.
•Deliver Measurable Wins: Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk.
•Build Systems and Tooling: Guide development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems.
•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.

Pay and Benefits

Salary: USD 230,000 - 322,000 annually

Perks:Health Insurance401kRemote WorkParental Leave

Key Requirements

•Deep ML engineering experience with hands-on work close to models (training, serving, optimization)
•Hands-on optimization background in training loops, serving systems, profiling workflows or GPU utilization
•Strong managerial ability with experience building and leading teams
•Distributed systems fluency and ability to reason about production-scale ML systems
•Ads/advertising ML experience or adjacency in production ML domains

Experience:AdvertisingMachine learningDigital advertising

Skills:PythonPyTorchGPUDistributed trainingProfilingBenchmarkingLoad testing

Languages:English

Tech Stack:PyTorchGPUDistributed systemsProfilingLoad testingBenchmarking

Company Brief

Operates Reddit, a large online community and discussion platform where users submit content, comment, and vote across topic-based communities (subreddits); monetizes via advertising, premium subscriptions, and awards.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2005

Website LinkedIn

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