Senior Machine Learning Engineer, ML Efficiency

Reddit, Inc.

Senior Engineer at Reddit managing Ads ML efficiency initiatives including training, inference, and system optimizations. Collaborating with teams to diagnose bottlenecks and mentor engineers.

Posted 7/24/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $216,700 - $303,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in optimizing machine learning systems for production environments, focusing on performance tooling, load testing, and operational readiness. Capable of mentoring engineers and driving complex projects with strong communication and collaboration skills.

Highest-signal resume keywords

Machine Learning Systems OptimizationPerformance Tooling DevelopmentLoad Testing and Fallback ReadinessCross-Team CollaborationTechnical Mentorship

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Optimization InitiativesProfilingBenchmarkingObservabilityTraining Efficiency ImprovementServing Efficiency ImprovementModel-Level OptimizationRuntime-Level OptimizationInfrastructure-Level OptimizationProject Ownership

Soft Skills

Strong CommunicationCustomer InstinctsProblem Solving

Tools & Technologies

Performance ToolingOptimization PlaybooksObservability Hooks

Industry Keywords

Ads ML WorkloadsOperational ConfidenceLatency VisibilityCost Visibility

About the role

Key responsibilities & impact

Independently own high-value optimization initiatives across training, inference, or launch-readiness for important Ads ML workloads.
Diagnose bottlenecks in real production systems using profiling, benchmarking, and observability rather than intuition-first debugging.
Build performance tooling, optimization playbooks, observability hooks, guardrails, or efficiency primitives that help more than one team or workload over time.
Improve launch-safety and efficiency readiness by contributing to load testing, fallback readiness, latency and cost visibility, and operational confidence for heavy models.
Work with model owners and platform teams to land pragmatic fixes while helping the team gradually standardize 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 strong execution habits.

Requirements

What you’ll need

Deep ML systems experience close to real production models and workloads, not just generic infra exposure.
Direct hands-on experience improving training or serving efficiency with measurable outcomes.
Strong technical judgment across model-level, runtime-level, and infrastructure-level optimization choices.
Ability to own complex projects end to end and collaborate effectively across team boundaries.
Good customer and platform instincts: can solve concrete bottlenecks while keeping maintainability, adoption, and future reuse in mind.
Strong communication: able to explain tradeoffs clearly to engineers and partner teams.

Benefits

Comp & perks

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