Lead ML Engineer, Ads Forecasting & Scenarios

Reddit; Oregon; Ibrido; USD 230.000 - 322.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health benefits

401k matching

Global benefits program

Family planning support

Gender-affirming care

Mental health & coaching

Flexible vacation & PTO

Parental leave

Descrizione del lavoro

Reddit is seeking a leader to build and own ML models that forecast campaign outcomes and inform advertisers’ decisions. You will lead cross-functional teams, drive technical directions, and deliver scalable modeling capabilities across planning and recommendations.

Ideal candidates have a strong background in predictive ML within advertising or marketplaces, with expertise in probabilistic forecasting, evaluation, and scalable production systems.

Competenze

• A track record of developing and shipping predictive ML systems in advertising, marketplaces, recommendations, search, demand forecasting, or similar complex domains.
• Strong foundations in statistical learning, probability, and optimization, with experience modeling large-scale behavioral or transactional data.
• Depth in 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.

Mansioni

• 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.

Descrizione del lavoro

Reddit is seeking a leader to build and own ML models that forecast campaign outcomes and inform advertisers’ decisions. You will lead cross-functional teams, drive technical directions, and deliver scalable modeling capabilities across planning and recommendations.

Ideal candidates have a strong background in predictive ML within advertising or marketplaces, with expertise in probabilistic forecasting, evaluation, and scalable production systems.