Staff Machine Learning Engineer, Ads Content Understanding

This is a fully remote position, open to applicants in United States.

📋 Description

• Provide technical guidance and mentorship to Machine Learning Engineers (MLEs) and Software Engineers (SWEs) engaged in ML projects within ACU, serving as the primary technical lead for content comprehension and signals: facilitating design reviews, establishing technical standards, and enhancing the team's modeling and systems expertise.

• Create evaluation frameworks and quality monitoring systems for content comprehension signals, utilizing state-of-the-art LM-judge methodologies.

• Promote operational excellence for ACU’s ML systems by defining Service Level Objectives (SLOs), implementing alerting mechanisms, and developing dashboards for critical signals (coverage, latency, precision/recall, cost).

• Develop and enhance content understanding capabilities for commercial interactions (e.g., reviews versus recommendations versus comparisons versus Q&A; sentiment and stance; product entities and categories) and operationalize them into reliable signals that drive contextual and shopping advertisements, auto-targeting, novel formats, and insights products.

• Lead the design and implementation of signals pipelines and create an ACU signals registry. Collaborate with platform teams and other content understanding teams to guarantee efficient and reliable service at Reddit's scale.

• Advocate for best practices in LLM and modern ML within ACU: determine when to prompt, fine-tune, or distill; design evaluation and safety harnesses; and spearhead at least one major distillation project to substitute external APIs with in-house models.

• Engage throughout the complete ML lifecycle (problem framing, data handling, model development, evaluation, deployment, monitoring, and on-call duties), crafting scalable, resilient MLOps pipelines and promoting responsible AI (addressing bias, safety, and explainability) for ACU’s models and signals in production.

⛳️ Requirements

• Over 7 years of pertinent MLE experience in delivering production ML systems (models + pipelines + serving) at scale, preferably in large-scale content understanding fields or advertising.

• Proven Staff-level technical leadership: has influenced architectural decisions, standards, and design reviews across various teams, and has aligned Product Managers (PMs), Data Scientists (DSs), and engineers on common ML systems or platforms without direct management authority.

• Exceptional communication skills, capable of articulating complex technical trade-offs to PMs, DSs, and other engineering teams, particularly in ambiguous, cross-team problem domains such as Seekers/Searchers monetization.

• Strong history of building and deploying NLP/Language models/content understanding models in production (e.g., classifiers, encoders, sequence or session models), achieving clear business results (e.g., CTR/ROAS improvements, safety enhancements). Experience with commercial or intent modeling is a significant advantage.

• Hands-on experience leveraging LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), managing quality, cost, and latency trade-offs.

• Extensive experience with PyTorch, TensorFlow, or similar frameworks, and producing high-quality code in Python (and ideally one statically typed language such as Go/Java/C++). Comfortable managing training, evaluation, and deployment code throughout the entire process.

• Experience in designing ML systems and pipelines: offline training, feature pipelines (both batch and streaming), online serving, monitoring, and experimentation for high-traffic environments.

🏝️ Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs

• 401k with Employer Match

• Global Benefit programs that align with your lifestyle, ranging from workspace arrangements to professional development and caregiving support

• Family Planning Assistance

• Gender-Affirming Care

• Mental Health & Coaching Benefits

• Flexible Vacation & Paid Volunteer Time Off

• Generous Paid Parental Leave