Jobs › Companies › Reddit › Staff Program Manager, Human & LLM Data Annotation Operations

About this Staff Program Manager, Human & LLM Data Annotation Operations role at Reddit

Reddit · Remote · Remote - United States
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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like.

Reddit is a network of thousands of communities where over 100 million daily active users dive into their interests, hobbies, and passions. Core to scaling our ads, and consumer experiences is high-quality, continuous data annotation. Our Operations ecosystem is expanding its central labeling engine to power models, taxonomies, and product experiments across both our Ads and Consumer Product organizations.

We are seeking a Staff Operations Program Manager (IC5) to serve as the strategic architect and operations lead for Reddit’s central data labeling function. In this high-visibility, 0-to-1 role, you will engage directly with product and technical teams across the company at all levels, to determine requirements and how best to execute these via our centralised function.

You will excel at translating complex, unstructured product needs into clear, scalable labeling directives that can be seamlessly executed by vendor teams and you will partner with our vendor partners to scale and optimize our delivery model.  In parallel, you will partner with cross functional leaders to define the future of automated, LLM-based labeling - positioning Reddit to leverage best in class technology and operations efficiencies.

Responsibilities:

  • Strategic Intake & Expectation Management: Strategic Intake & Expectation Management: Own and scale the incoming request process across Consumer and Ads. Ensure delivery frameworks are robust and reliable, and that all initiatives are prioritised appropriately, based on agreed criteria and business impact.
  • 0-to-1 Operations & LLM Scaling: Take full ownership of shaping how the central labeling function grows; design and execute the operational roadmap to integrate LLM-assisted labeling workflows to augment human vendors and multiply throughput.
  • Taxonomy & Experimentation Architecture: Standardize taxonomy definition guidelines and operationalize complex, multi-quarter labeling projects supporting Consumer Org product experiments and Ads Org safety systems.
  • Cross-Functional Alignment: Partner directly with Product Managers, Data Scientists, and Ops Leaders across orgs to align labeling capabilities with broader business objectives, translating high-level concepts into executable human and machine tasks.
  • Guideline & Operational Calibration: Partner with our dedicated Vendor Manager to hand off clear task guidelines, resolve complex edge cases, and establish feedback loops that ensure task performance aligns with product expectations.
  • Framework Development: Build, document, and standardize centralized request intake models, SLA frameworks, quality assurance practices, and throughput metrics across all labeling domains.

Required Qualifications:

  • 7+ years of experience in data operations, program management, or vendor operations with a heavy focus on data labeling, model training data, or taxonomy infrastructure.
  • Stakeholder Management & Leadership: Proven ability to align Product and Engineering leadership, skilled at setting firm boundaries, and enforcing structured prioritization.
  • Translation & Taxonomy Mastery: Exceptional ability to translate vague product requirements into detailed, unambiguous labeling instructions, edge-case trees, and taxonomy classification schemas.
  • LLM & Automation Integration: Experience leveraging LLMs, synthetic data generation, or automated tooling to augment traditional vendor annotation workflows and scale operational capacity.
  • Operational Collaboration: Demonstrated ability to partner effectively with internal Vendor Operations/Managers to translate project requirements into executable guidelines and handle task-level escalations.

Preferred Qualifications:

  • Experience navigating cross-functional dynamics across both Ads/Monetization and Consumer-facing product organizations.
  • Strong proficiency in SQL and data manipulation to independently analyze vendor quality metrics, pipeline throughput, and project completion SLAs.


Benefits:

  • 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 

 

 

#LI-SP1

Pay Transparency:

This job 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. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is:
$180,200—$252,300 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

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How this Data Annotator salary compares

This role pays $216,250/yr — above the typical range for Data Annotator roles.

$18,720 median $44,601 $52,520

Typical range $34,685–$44,720/yr, from 40 comparable Data Annotator listings on JobsRadar (pay annualized to USD). See Data Annotator salary insights →

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