Senior ML Engineer, Ads Content Understanding (Remote)

Quiet Capital; United States; On-site; USD 216,700 - 303,400; Full time

Benefits offered by this job

Healthcare benefits

401k with employer match

Global benefits

Family planning support

Gender-affirming care

Mental health benefits

Flexible vacation & volunteer time

Parental leave

Job summary

Reddit is seeking a Senior Machine Learning Engineer (IC4) to join the Content Understanding team within ACU. This role emphasizes applied ML with emphasis on scalable systems, monetization signals, and pragmatic ML throughput rather than pure research.

You will guide ML lifecycle design, drive SLOs and monitoring, mentor peers, and push LLM-based and traditional models to production, delivering measurable business impact.

Qualifications

• 5+ years of relevant MLE experience delivering production ML systems.
• Experience contributing to architecture decisions, standards, and design reviews.
• Ability to explain complex trade-offs to PMs, DSs, and other engineers.
• Experience shipping NLP/Language models to production with business outcomes.

Responsibilities

• Design scalable ML pipelines and champion responsible AI for ACU’s models in production.
• Provide technical leadership and mentorship to MLEs and SWEs.
• Develop evaluation and quality monitoring systems for content understanding signals.
• Define SLOs, alerts, and dashboards for key signals (coverage, latency, precision/recall, cost).
• Evolve content understanding capabilities for commercial conversations and power signals for ads and insights.

Skills

MLE experience

Technical leadership

Communication

NLP/Language models

Tools

PyTorch

TensorFlow

Python

Go/Java/C++

Job description

Reddit is seeking a Senior Machine Learning Engineer (IC4) to join the Content Understanding team within ACU. This role emphasizes applied ML with emphasis on scalable systems, monetization signals, and pragmatic ML throughput rather than pure research.

You will guide ML lifecycle design, drive SLOs and monitoring, mentor peers, and push LLM-based and traditional models to production, delivering measurable business impact.