bluedoor data·Job Postings API·bluedoor.sh ↗

HomeCompaniesRedditStaff Machine Learning Engineer, Ads Content Understanding

Staff Machine Learning Engineer, Ads Content Understanding

Reddit · Remote - United States · Remote · Active · Greenhouse

Job facts

FieldValue
CompanyReddit
TitleStaff Machine Learning Engineer, Ads Content Understanding
Normalized title-
Department / teamAds Engineering
LocationUnited States
Work modelRemote / Remote
Employment type-
SalarySalary
Statusactive
ATS providerGreenhouse
Posted / first seen2026-04-24 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Reddit.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Ads Engineering.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyReddit
Source1b5f7232-3035-4e19-b28e-52cc5e96c57e
ATS providerGreenhouse

Description

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 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . 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). Responsibilities: 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. Required Qualifications: 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. 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-Remote 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: $230,000 — $322,000 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.

Full job record

Job IDa3c82215318863b2cb1c637b1e03d426329ad0c8
Org ID75711b72-973a-4ca5-9542-6e4d2b9d0be5
Source ID1b5f7232-3035-4e19-b28e-52cc5e96c57e
Board ID1b5f7232-3035-4e19-b28e-52cc5e96c57e
Providergreenhouse
Provider Job Key7851761
TitleStaff Machine Learning Engineer, Ads Content Understanding
Normalized Title
Statusactive
Activeyes
Location TextRemote - United States
DepartmentAds Engineering
Team
Employment Type
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary RawSalary
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://job-boards.greenhouse.io/reddit/jobs/7851761
Apply URLhttps://job-boards.greenhouse.io/reddit/jobs/7851761
First Seen At2026-05-29 22:40:12Z
Last Seen At2026-06-06 19:26:18Z
Last Checked At2026-06-06 19:26:18Z
Last Changed At2026-05-29 22:40:12Z
Inactive At
Source Posted At2026-04-24 18:21:49Z
Source Updated At2026-05-14 18:49:55Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=reddit/date=2026-06-06/2026-06-06T19-26-18-274Z-d4957c40d6f24bbd0751467ad4ef383175f0cfac1bd5d074b08377debf73a3e9.json
Event Fields
{
  "content_hash": "d4f7125a8043bd834a6a912c9c32c26211b6ce3d2a28511a9adc9cb6ef3de783",
  "source_hash": "58f44e5a917df047a7bfa89bd25632d5d27dec4b767672a1e6f8f520dd121b55",
  "last_changed_at": "2026-05-29T22:40:12.303Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "Remote - United States",
    "city": null,
    "region": null,
    "country": "United States",
    "is_remote": true,
    "confidence": 0.95
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-06T19:26:18.729Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "Remote - United States",
      "city": null,
      "region": null,
      "country": "United States",
      "is_remote": true,
      "confidence": 0.95
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "remote",
  "salary_period": null,
  "workplace_type": "remote",
  "salary_currency": null
}
Extensions
{}
Native Structured
{
  "title": "Staff Machine Learning Engineer, Ads Content Understanding",
  "offices": [
    {
      "id": 88237,
      "name": "Remote - United States",
      "location": null,
      "child_ids": [],
      "parent_id": null
    }
  ],
  "language": "en",
  "location": {
    "name": "Remote - United States"
  },
  "metadata": [
    {
      "id": 944668,
      "name": "Position ID",
      "value": "P-100797",
      "value_type": "short_text"
    },
    {
      "id": 956352,
      "name": "Recruiting Start Date",
      "value": "2026-04-24",
      "value_type": "date"
    },
    {
      "id": 944671,
      "name": "Target Hire Date",
      "value": "2026-07-31",
      "value_type": "date"
    },
    {
      "id": 944672,
      "name": "Target Hire End Date",
      "value": "",
      "value_type": "date"
    },
    {
      "id": 944673,
      "name": "Job Profile",
      "value": "Machine Learning Engineer 5",
      "value_type": "single_select"
    },
    {
      "id": 956351,
      "name": "Management Level",
      "value": "IC5",
      "value_type": "single_select"
    },
    {
      "id": 944675,
      "name": "Job Family",
      "value": "Machine Learning",
      "value_type": "single_select"
    },
    {
      "id": 53341,
      "name": "Worker Sub-Type",
      "value": "Regular",
      "value_type": "single_select"
    },
    {
      "id": 944676,
      "name": "Time Type",
      "value": "Full time",
      "value_type": "single_select"
    },
    {
      "id": 944682,
      "name": "Pay Rate Type",
      "value": "Salary",
      "value_type": "single_select"
    },
    {
      "id": 944681,
      "name": "Scheduled Weekly Hours",
      "value": "40.0",
      "value_type": "number"
    },
    {
      "id": 944667,
      "name": "Company",
      "value": "Reddit, Inc.",
      "value_type": "single_select"
    },
    {
      "id": 944677,
      "name": "Cost Center",
      "value": "Tech-Ads Engineering",
      "value_type": "single_select"
    },
    {
      "id": 944669,
      "name": "Worker Type",
      "value": "Employee",
      "value_type": "single_select"
    },
    {
      "id": 957961,
      "name": "Department",
      "value": null,
      "value_type": "single_select"
    }
  ],
  "updated_at": "2026-05-14T14:49:55-04:00",
  "departments": [
    {
      "id": 70548,
      "name": "Ads Engineering",
      "child_ids": [],
      "parent_id": 16253
    }
  ],
  "company_name": "Reddit",
  "requisition_id": 3421280,
  "first_published": "2026-04-24T14:21:49-04:00",
  "application_deadline": null
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/a3c82215318863b2cb1c637b1e03d426329ad0c8?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/75711b72-973a-4ca5-9542-6e4d2b9d0be5JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/1b5f7232-3035-4e19-b28e-52cc5e96c57eJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/a3c82215318863b2cb1c637b1e03d426329ad0c8/eventsJSON