Senior Machine Learning Engineer, Ads Forecasting & Scenarios
New
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Reddit, Inc.Advertising technology
Remote - United StatesFull-TimeSenior
SalaryThe base salary range for this position is: $216,700 — $303,400 USD
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Job Details
- Required Skills
- PythonMachine Learning
Requirements
- Independently design, ship, and improve predictive ML systems in advertising, marketplaces, recommendations, search, forecasting, or similarly complex domains.
- Have strong foundations in statistical learning, probability, and optimization.
- Have experience working with large-scale behavioral or transactional data.
- Bring practical experience in forecasting, response prediction, probabilistic modeling, multitask learning, or transfer learning.
- Apply sound evaluation judgment, including temporal validation and segment-level analysis.
- Understand calibration, uncertainty, and the limits of predictions under changed conditions.
- Diagnose and address sparse observations, cold start, seasonality, distribution shift, selection bias, or delayed labels.
- Demonstrate strong programming and software engineering skills, including building and operating production ML pipelines and services.
- Turn ambiguous product questions into concrete technical plans and lead projects through rollout.
- Collaborate effectively across functions.
Responsibilities
- Translate advertiser questions into modeling problems involving delivery, reach, performance, and investment tradeoffs.
- Connect signals about advertising opportunities, audience activity, marketplace competition, and predicted response to estimate campaign outcomes.
- Build and improve models that estimate the effects of changes in budget, bid, audience, or optimization objective.
- Incorporate partner-team predictions, including creative-performance estimates, to evaluate potential campaign improvements.
- Develop approaches for sparse segments, cold start, seasonality, delayed feedback, and changing marketplace conditions.
- Evaluate forecast accuracy, calibration, uncertainty, and performance across advertiser cohorts; document assumptions and limitations.
- Compare predictions with mature outcomes, investigate systematic errors, and use experiments and observed results to improve forecasts.
- Own model training, inference, monitoring, and iteration; collaborate with partner teams and contribute to design and code reviews.
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