Senior Machine Learning Engineer, Ads Forecasting & Scenarios
About The Position
Reddit is hiring a Senior Machine Learning Engineer on its Ads Forecasting & Scenarios team. The role builds machine learning capabilities that help advertisers understand potential outcomes on Reddit and make informed investment decisions. The engineer develops models to estimate how campaign results may change with different budgets, bids, audiences, creative performance, or objectives, connecting supply and demand forecasting, audience availability, and response prediction. This is a hands-on role with end-to-end ownership of forecasting models and production capabilities, from problem formulation and technical design through evaluation, deployment, and iteration. The engineer works with engineers and cross-functional partners to develop reliable forecasts, evaluate scenario comparisons, and improve models using mature campaign outcomes and experiments. The successful candidate will independently deliver and operate forecasting capabilities that improve accuracy and calibration for priority advertiser populations. Their models should support credible comparisons of campaign alternatives, have clear evaluation and monitoring, and help advertisers make better planning and investment decisions.
Requirements
- Experience independently designing, shipping, and improving predictive machine-learning systems in advertising, marketplaces, recommendations, search, forecasting, or similarly complex domains.
- Strong foundations in statistical learning, probability, and optimization, with experience working with large-scale behavioral or transactional data.
- Practical experience in at least one relevant area, such as forecasting, response prediction, probabilistic modeling, multitask learning, or transfer learning.
- Sound evaluation judgment, including temporal validation, segment-level analysis, and understanding of calibration, uncertainty, and the limits of predictions under changed conditions.
- Experience diagnosing and addressing modeling challenges such as sparse observations, cold start, seasonality, distribution shift, selection bias, or delayed labels.
- Strong programming and software engineering skills, including experience building and operating production ML pipelines and services.
- Demonstrated ability to turn ambiguous product questions into concrete technical plans, lead projects through rollout, and collaborate effectively across functions.
Nice To Haves
- Experience with demand, supply, and inventory forecasting, such as advertising inventory, marketplace demand, traffic, retail demand, or capacity forecasting, including time-series methods, hierarchical or global models, and multi-horizon prediction.
- Experience with auction and investment modeling, such as auction simulation or replay, win-rate and price prediction, bid or budget response curves, or constrained optimization.
- Experience with scenario evaluation, such as counterfactual or off-policy evaluation, sensitivity analysis, uncertainty propagation, or combining predictive models to estimate campaign outcomes.
- Experience with reach and audience estimation, such as population and overlap estimation, reach/frequency models, sampling correction, or saturation modeling.
- Experience with probabilistic and response modeling, such as quantile or distributional prediction, calibrated conversion/value prediction, or delayed-feedback modeling.
Responsibilities
- Own forecasting and scenario-modeling projects, translating advertiser questions into modeling problems involving delivery, reach, performance, and investment tradeoffs.
- Develop technical approaches, make practical tradeoffs, and drive project execution.
- Connect signals about available advertising opportunities, audience activity, marketplace competition, and predicted response to improve estimates of achievable campaign outcomes.
- Build and improve models that estimate the effects of changes in budget, bid, audience, or optimization objective, accounting for auction dynamics and campaign constraints.
- Incorporate predictions from partner teams, including creative-performance estimates, to assess potential improvements in delivery, efficiency, or advertiser value.
- Improve model generalization for sparse segments, cold start, seasonality, delayed feedback, and changing marketplace conditions while balancing predictive quality, complexity, and production requirements.
- Evaluate forecast accuracy, calibration, uncertainty, and performance across advertiser cohorts; document assumptions and limitations; and work with partners to determine which scenario comparisons are supported by evidence.
- Compare predictions with mature outcomes, investigate systematic errors, and use experiments and observed results to improve forecasts and validate scenario estimates.
- Own model training, inference, monitoring, and iteration in production.
- Collaborate with Product, Data Science, Ads Delivery, Audience, and Creative teams; contribute to design and code reviews; and mentor engineers through project work.
Benefits
- Comprehensive healthcare benefits and income replacement programs
- 401(k) with employer match
- Global benefit programs covering workspace, professional development, and caregiving support
- Family planning support
- Gender-affirming care
- Mental health and coaching benefits
- Flexible vacation and paid volunteer time off
- Generous paid parental leave
- Equity in the form of restricted stock units
- Possible commission depending on the position offered
- Medical, dental, and vision insurance for U.S.-based employees
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
