Strategic Overview
Staff Machine Learning Engineer, Ads Forecasting & Scenarios at Reddit is defined by the responsibilities and candidate requirements in the employer's listing.
The published role emphasizes work such as Lead forecasting and scenario modeling. Translate advertiser questions into models of delivery, reach, performance, and investment tradeoffs. Set technical direction and guide execution across the team.
The role is listed for United States with a remote working arrangement, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
The opportunity
Build the machine learning capabilities that help advertisers understand what they could achieve on Reddit and make better investment decisions.
You will lead models that estimate how campaign outcomes could change with different budgets, bids, audiences, creative performance, or objectives. The work connects supply and demand forecasting, audience availability, response prediction, and marketplace simulation to help advertisers compare alternatives and recognize valuable opportunities they may be missing.
Key Responsibilities & Objectives
- Lead forecasting and scenario modeling. Translate advertiser questions into models of delivery, reach, performance, and investment tradeoffs. Set technical direction and guide execution across the team.
- Connect inventory, demand, and response. Combine forecasts of available advertising opportunities, audience activity, marketplace competition, and predicted response to estimate achievable delivery and performance.
- Estimate outcomes under alternative choices. Develop models that account for changes in budget, bid, audience, and optimization objective, including interactions among these choices, auction dynamics, and campaign constraints.
- Quantify unrealized opportunity. Incorporate creative-performance estimates from partner teams to assess how stronger creative could have improved campaign results. Translate those inputs into potential gains in delivery, efficiency, or advertiser value.
- Build models that generalize. Apply probabilistic forecasting, multitask learning, transfer learning, hierarchical modeling, or related approaches to handle sparse segments, cold start, delayed feedback, and changing conditions.
- Establish trustworthy comparisons. Evaluate numerical accuracy, calibration, uncertainty, and cohort-level performance. Define supported scenarios and identify when additional evidence or experimentation is needed.
- Close the learning loop. Compare recorded predictions with mature outcomes, diagnose systematic errors, and validate scenario estimates through experiments and observed results.
- Own production delivery and technical leadership. Partner with engineers on reliable training, serving, monitoring, and iteration. Lead designs, mentor engineers, and collaborate with Product, Data Science, Ads Delivery, Audience, and Creative teams.
Required Qualifications & Candidate Blueprint
- A track record of developing and shipping predictive ML systems in advertising, marketplaces, recommendations, search, demand forecasting, or similarly complex domains.
- Strong foundations in statistical learning, probability, and optimization, with experience modeling large-scale behavioral or transactional data.
- Depth in one or more relevant areas: probabilistic or hierarchical forecasting, calibrated conversion/value prediction, multitask or transfer learning, delayed-feedback or survival modeling, or response modeling .
- Strong judgment in evaluation, including temporal validation, calibration, segment-level performance, and the assumptions required to estimate outcomes under changed conditions.
- Experience addressing sparse observations, cold start, seasonality, distribution shift, selection bias, or partially observed labels.
- Strong programming and software engineering skills, including experience building and operating production ML systems.
- Demonstrated ability to lead ambiguous technical initiatives, make practical tradeoffs, and develop other engineers.
Preferred Qualifications
- Demand, supply, and inventory forecasting: Advertising inventory, marketplace demand, traffic, retail demand, or capacity forecasting. Relevant methods include probabilistic time-series models, hierarchical/global forecasting, external-signal modeling, and multi-horizon prediction.
- Auction and investment modeling: Auction simulation or replay, conditional win-rate and price models, bid/budget response curves, or constrained optimization.
- Scenario evaluation: Counterfactual or off-policy evaluation, sensitivity analysis, uncertainty propagation, or composition of multiple predictive models.
- Reach and audience estimation: Population and overlap estimation, probabilistic reach/frequency models, sampling correction, or saturation modeling.
- Advanced predictive methods: Mixture-of-experts, distributional or quantile prediction, temporal sequence models, or state-space models.
Salary & Benefits
Published compensation: $230,000 – $322,000 USD
- 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
Salary Benchmark
This role’s published compensation is compared with active employer-disclosed ranges for the same role at the Staff level, in the same currency and pay period.
Benchmark uses active employer job postings in our database, excludes this listing, and matches the currency and pay period. It is not a third-party salary estimate; currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
The opportunity
Build the machine learning capabilities that help advertisers understand what they could achieve on Reddit and make better investment decisions.
You will lead models that estimate how campaign outcomes could change with different budgets, bids, audiences, creative performance, or objectives. The work connects supply and demand forecasting, audience availability, response prediction, and marketplace simulation to help advertisers compare alternatives and recognize valuable opportunities they may be missing.
This is a hands-on technical leadership role with ownership of modeling direction, evaluation standards, and reusable production capabilities across advertiser planning and recommendations.
What you’ll do
- Lead forecasting and scenario modeling. Translate advertiser questions into models of delivery, reach, performance, and investment tradeoffs. Set technical direction and guide execution across the team.
- Connect inventory, demand, and response. Combine forecasts of available advertising opportunities, audience activity, marketplace competition, and predicted response to estimate achievable delivery and performance.
- Estimate outcomes under alternative choices. Develop models that account for changes in budget, bid, audience, and optimization objective, including interactions among these choices, auction dynamics, and campaign constraints.
- Quantify unrealized opportunity. Incorporate creative-performance estimates from partner teams to assess how stronger creative could have improved campaign results. Translate those inputs into potential gains in delivery, efficiency, or advertiser value.
- Build models that generalize. Apply probabilistic forecasting, multitask learning, transfer learning, hierarchical modeling, or related approaches to handle sparse segments, cold start, delayed feedback, and changing conditions.
- Establish trustworthy comparisons. Evaluate numerical accuracy, calibration, uncertainty, and cohort-level performance. Define supported scenarios and identify when additional evidence or experimentation is needed.
- Close the learning loop. Compare recorded predictions with mature outcomes, diagnose systematic errors, and validate scenario estimates through experiments and observed results.
- Own production delivery and technical leadership. Partner with engineers on reliable training, serving, monitoring, and iteration. Lead designs, mentor engineers, and collaborate with Product, Data Science, Ads Delivery, Audience, and Creative teams.
What we’re looking for
- A track record of developing and shipping predictive ML systems in advertising, marketplaces, recommendations, search, demand forecasting, or similarly complex domains.
- Strong foundations in statistical learning, probability, and optimization, with experience modeling large-scale behavioral or transactional data.
- Depth in one or more relevant areas: probabilistic or hierarchical forecasting, calibrated conversion/value prediction, multitask or transfer learning, delayed-feedback or survival modeling, or response modeling.
- Strong judgment in evaluation, including temporal validation, calibration, segment-level performance, and the assumptions required to estimate outcomes under changed conditions.
- Experience addressing sparse observations, cold start, seasonality, distribution shift, selection bias, or partially observed labels.
- Strong programming and software engineering skills, including experience building and operating production ML systems.
- Demonstrated ability to lead ambiguous technical initiatives, make practical tradeoffs, and develop other engineers.
Preferred experience
Complementary depth in one or more of:
- Demand, supply, and inventory forecasting: Advertising inventory, marketplace demand, traffic, retail demand, or capacity forecasting. Relevant methods include probabilistic time-series models, hierarchical/global forecasting, external-signal modeling, and multi-horizon prediction.
- Auction and investment modeling: Auction simulation or replay, conditional win-rate and price models, bid/budget response curves, or constrained optimization.
- Scenario evaluation: Counterfactual or off-policy evaluation, sensitivity analysis, uncertainty propagation, or composition of multiple predictive models.
- Reach and audience estimation: Population and overlap estimation, probabilistic reach/frequency models, sampling correction, or saturation modeling.
- Advanced predictive methods: Mixture-of-experts, distributional or quantile prediction, temporal sequence models, or state-space models.
What success looks like
Accurate and calibrated forecasts across priority advertiser populations; credible comparisons of supported campaign alternatives; reusable capabilities across planning and recommendations; and evidence that advertisers identify valuable opportunities and make better investment decisions.
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
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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
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.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This opening may suit candidates who can demonstrate experience relevant to the employer's published requirements. Its strongest career signal is the scope of the work itself — particularly Lead forecasting and scenario modeling. Translate advertiser questions into models of delivery, reach, performance, and investment tradeoffs. Set technical direction and guide execution across the team. — rather than a generic title alone.
Resume & Application Strategy
For the application, connect specific examples from your experience to the responsibilities and qualifications in the employer's description. Quantify outcomes from comparable work, and place the most relevant evidence near the top of the resume. When the employer explicitly names tools, platforms, leadership scope, or domain experience, use those source terms accurately and in context.
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