Staff Machine Learning Engineer, Ads Forecasting & Scenarios

Details

Reddit is seeking a hands-on technical leader to build machine learning capabilities that help advertisers understand potential outcomes on Reddit and make better investment decisions. The role focuses on modeling how campaign outcomes may change with different budgets, bids, audiences, creative performance, and objectives. It connects supply and demand forecasting, audience availability, response prediction, and marketplace simulation to support advertiser planning and recommendations.

Responsibilities

• Lead forecasting and scenario modeling for delivery, reach, performance, and investment tradeoffs.
• Set technical direction and guide execution across the team.
• Combine forecasts of advertising opportunities, audience activity, marketplace competition, and predicted response.
• Model alternative budgets, bids, audiences, and optimization objectives, including auction dynamics and campaign constraints.
• Quantify unrealized opportunity by incorporating creative-performance estimates and translating them into potential gains in delivery, efficiency, or advertiser value.
• Build generalizable models using probabilistic forecasting, multitask learning, transfer learning, hierarchical modeling, or related approaches.
• Address sparse segments, cold starts, delayed feedback, and changing conditions.
• Establish evaluation standards for numerical accuracy, calibration, uncertainty, and cohort-level performance.
• Compare predictions with mature outcomes, diagnose systematic errors, and validate scenario estimates through experiments and observed results.
• 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.

Requirements

• Track record of developing and shipping predictive machine learning systems in advertising, marketplaces, recommendations, search, demand forecasting, or similarly complex domains.
• Strong foundations in statistical learning, probability, and optimization.
• Experience modeling large-scale behavioral or transactional data.
• Depth in one or more of probabilistic or hierarchical forecasting, calibrated conversion or value prediction, multitask or transfer learning, delayed-feedback or survival modeling, and response modeling.
• Strong evaluation judgment, including temporal validation, calibration, segment-level performance, and assumptions for estimating outcomes under changed conditions.
• Experience addressing sparse observations, cold starts, seasonality, distribution shift, selection bias, or partially observed labels.
• Strong programming and software engineering skills, including experience building and operating production ML systems.
• Ability to lead ambiguous technical initiatives, make practical tradeoffs, and develop other engineers.

Preferred Experience

• Demand, supply, and inventory forecasting, including probabilistic time-series models, hierarchical or global forecasting, external-signal modeling, and multi-horizon prediction.
• Auction and investment modeling, including auction simulation or replay, conditional win-rate and price models, bid or budget response curves, and constrained optimization.
• Scenario evaluation, including counterfactual or off-policy evaluation, sensitivity analysis, uncertainty propagation, and composition of multiple predictive models.
• Reach and audience estimation, including population and overlap estimation, probabilistic reach or frequency models, sampling correction, and saturation modeling.
• Advanced predictive methods such as mixture-of-experts, distributional or quantile prediction, temporal sequence models, and state-space models.

Success Metrics

Success includes 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.
• 401(k) with employer match.
• Global benefit programs supporting workspace, professional development, and caregiving.
• Family planning support.
• Gender-affirming care.
• Mental health and coaching benefits.
• Flexible vacation and paid volunteer time off.
• Generous paid parental leave.

Compensation

The base salary range is $230,000–$322,000 USD. The position is also eligible for equity in the form of restricted stock units and, depending on the position offered, may be eligible for a commission. Reddit provides additional benefits to U.S.-based employees, including medical, dental, and vision insurance, a 401(k) program with employer match, vacation, and parental leave. Final offer amounts depend on skills, experience, and other factors.