Senior Machine Learning Manager - Ads Content Understanding

at Reddit
USD 266,000-372,400 per year
SENIOR
✅ Remote

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Marketing @ 4 Go @ 4 Kafka @ 4 Kubernetes @ 4 Redis @ 4 Python @ 4 Spark @ 4 Java @ 4 Flink @ 4 Machine Learning @ 4 Hiring @ 4 Communication @ 4 MongoDB @ 4 API @ 4 Reporting @ 4 NLP @ 4 LLM @ 4 Cassandra @ 4

Details

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information.

The Ads Content Understanding team is a foundational team in Ads Monetization in charge of designing, building, and selecting state of the art techniques to deliver interpretable signals associated with Reddit organic and business content (posts, comments, ads, creatives, linked content/media).

Signals & Content understanding infrastructure produced by this team is at the core of our Ads Marketplace AI, our Community Intelligence Engine & Ads Insights capabilities, and the key systems that power all our Reddit Monetization products. This team is a central investment for Reddit Monetization efforts to highlight one of our biggest differentiators in the internet: genuinely curated, high quality, extremely relevant, and daily updated organic & commercial content. We are a Machine Learning/Data heavy team with a focus in the following areas:

  • Knowledge Graph — Semi-automatic curation, expansion, and utilization of Reddit’s knowledge database, NLP tokenization, NER models, disambiguation systems at entity level
  • Contextual Signals — Make sense of Posts, Landing pages, Ads Placements, Organic Topics using team owned engines in combination with other Reddit content understanding teams
  • Marketplace Efficiency — Helping Ads Targeting, Ranking, Quality, & Measurement to deliver best in class performance leveraging our interpretable signals directly or indirectly with our partner semantic representations and feature engineering teams
  • Business & Community Intelligence Applications — Bring Contextual Signals (Web, APIs, Custom Reporting) to our Advertisers to empower a new generation of Business Intelligence and help Brands understand Reddit better

We are looking for a Senior Engineering Manager with industry-relevant ML expertise to lead the Ads Content Understanding team composed of MLEs, SWEs, and Data experts across US & EU geos.

Responsibilities

  • Coach, motivate, build, hire, and lead a world-class team of ML practitioners, experts, and engineers
  • Lead, coordinate, and execute a coherent vision for a robust roadmap of Commercial Content Understanding capabilities to unlock a fully context aware Ads Monetization system (Platform + Marketplace) and support with authentically unique Business Intelligence insights for Ads Sales and Marketing
  • Set and support a culture of data-informed decision making, with efficient processes and strong transparency
  • Facilitate collaboration between the different Content Understanding platforms in use across Reddit with an eye towards platform & signal consolidations
  • Raise the bar across modeling & exploration phases in the Content Understanding space
  • Collaborate with cross-functional team leads (EMs, PMs, DSs) to understand business requirements and translate them into technical directions

Requirements

Required Qualifications:

  • 8+ years of industry experience as a SWE, DSM, or MLE
  • 6+ years managing engineers
  • 2+ years managing MLEs
  • Experience with at least two general programming languages such as Python, Go, Java, C++
  • Preferred experience in one or more of: Message Queuing Services (Kafka, Amazon Simple Queue Service), Data Processing Frameworks (Apache Spark, Apache Flink), Key Value Stores (Redis, DynamoDB), Document based DBs (MongoDB, Cassandra), Container Orchestration (Kubernetes, Mesos), ML Ops ((ML | Tensor | Kube)flow)
  • Excellent communication skills, both written and verbal, and the ability to work effectively with product managers, data scientists, and other stakeholders

Preferred Qualifications:

  • Experience managing ML heavy engineering teams
  • Experience with Ads
  • Experience with Natural Language Understanding (ML science and infra)
  • Industry relevant scientific contribution in the field of NLP and Content Understanding
  • Experience with LLM in the context of multimodal Content Understanding
  • This role offers flexibility and is remote-friendly - however, it is highly preferred that the candidate is based in the proximity of the SF Bay Area office (Pacific time) or the NYC office (Eastern time).

Benefits

  • Comprehensive Healthcare Benefits
  • 401k Matching
  • Workspace benefits for your home office
  • Personal & Professional development funds
  • Family Planning Support
  • Flexible Vacation & Reddit Global Wellness Days
  • 4+ months paid Parental Leave
  • Paid Volunteer time off

Pay Transparency & Additional Info

  • This posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission.
  • The base pay range for this position is: $266,000 - $372,400 USD
  • In select roles and locations, interviews will be recorded, transcribed and summarized by AI; candidates may opt out prior to scheduled interviews. During interviews Reddit will collect identifiers, professional/employment information, sensory information (audio/video), and any other candidate-shared categories necessary to evaluate the application. Recordings will be deleted after hiring decisions as described in Reddit’s Candidate Privacy Policy.
  • Reddit is an equal opportunity employer and is committed to reasonable accommodations for qualified individuals with disabilities.

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