Senior Ads ML Efficiency Engineer

EngineersOfAI; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Reddit is building a dedicated Ads ML Efficiency function to accelerate model training, inference, and serving with measurable improvements. You will own optimization initiatives across training, inference, and launch-readiness, collaborating with ranking teams, serving owners, and ML Platform to land practical, reusable fixes.

You will mentor engineers, drive observability, and help standardize patterns across workloads to improve latency and cost visibility while maintaining launch safety.

Qualifications

• Deep ML systems experience close to production models.
• Hands-on experience improving training or serving efficiency with measurable outcomes.
• Strong technical judgment across model-, runtime-, and infra-level optimization choices.
• Ability to own complex projects end-to-end and collaborate across team boundaries.
• Good customer and platform instincts: solve concrete bottlenecks with maintainability in mind.
• Strong communication: explain tradeoffs clearly to engineers and partner teams.

Responsibilities

• Independently own high-value optimization initiatives across training, inference, or launch-readiness for Ads ML workloads.
• Diagnose bottlenecks in real production systems using profiling, benchmarking, and observability.
• Build performance tooling, optimization playbooks, observability hooks, guardrails, or efficiency primitives.
• Improve launch-safety and efficiency readiness by contributing to load testing, fallback readiness, latency and cost visibility, and operational confidence.
• Work with model owners and platform teams to land pragmatic fixes while standardizing repeated solutions.
• Contribute to the team’s technical direction by surfacing patterns, tradeoffs, and opportunities for reuse or automation.
• Mentor less-experienced engineers through code, debugging, measurement rigor, and execution habits.

Skills

ML systems

Optimization

Technical judgment

End-to-end ownership

Customer/platform instincts

Communication

Job description

Reddit is building a dedicated Ads ML Efficiency function to accelerate model training, inference, and serving with measurable improvements. You will own optimization initiatives across training, inference, and launch-readiness, collaborating with ranking teams, serving owners, and ML Platform to land practical, reusable fixes.

You will mentor engineers, drive observability, and help standardize patterns across workloads to improve latency and cost visibility while maintaining launch safety.