Staff Machine Learning Engineer, Reddit
Ads Content Understanding
$230-322k
+ Restricted stock units
Online platform for thoughts, experiences and discussions
Be an early applicant
Online platform for thoughts, experiences and discussions
1001+ employees
Be an early applicant
$230-322k
+ Restricted stock units
1001+ employees
Company mission
To empower communities, and make their knowledge accessible to all.
Role
Who you are
- 7+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads
- Demonstrated Staff-level technical leadership: has driven architecture decisions, standards, and design reviews across multiple teams, and has aligned PMs, DSs, and engineers on shared ML systems or platforms without direct people-management authority
- Excellent communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization
- Strong track record building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus
- Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs
- Deep experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one statically typed language like Go/Java/C++). Comfortable owning training, evaluation, and deployment code end-to-end
- Experience designing ML systems and pipelines: offline training, feature pipelines (batch/streaming), online serving, monitoring, and experimentation for high-traffic surfaces
What the job involves
- Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:
- The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources)
- Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics
- Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations
- Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs
- Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams
- We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems
- Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems)
- Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft
- Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices
- Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
- Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products
- Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale
- Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models
- Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production
Our take
Reddits is an online platform that hosts thousands of message board communities (known as subreddits) designed to foster authentic human connection. With more than 100,000 communities covering everything from food, entertainment, and sports to niche interests for highly specific audiences, there's virtually a space for everyone.
The platform attracts over 52M daily users and more than 50B monthly page views. While these figures are smaller than those of social media giants like Facebook and X, Reddits stands out by offering easily discoverable communities where users can dive deep into virtually any topic imaginable.
Today, Reddit continues to grow its user base and expand its reach, remaining a unique hub for conversation,m connection, and shared interests. With its strong community-driven model and steady revenue streams, it's most definitely positioned to stay a central part of online culture for years to come.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
57% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Aug 2021
$410m
SERIES F
Feb 2021
$250m
SERIES E
Total funding: $1.2bn
Company benefits
- Comprehensive health benefits
- Flexible vacation & Reddit global days off
- Family planning funds & 4+ months paid parental leave
- Personal & professional development funds
- Paid volunteer time off
- Workspace & home office benefits
Company HQ
SoMa, San Francisco, CA
Leadership
Steve Huffman
(Co-Founder & CEO)After co-founding Reddit in 2005, they stepped away from the company to co-found Hipmunk, where they were the CTO for 5 years. They returned to Reddit in 2015, and have been the CEO since.
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