Senior Machine Learning Engineer, Ads Forecasting & Scenarios

Location: Remote - United States

Base salary: $216,700–$303,400 USD per year, plus potential equity and, depending on the position, commission.

Company

Community platform with more than 100,000 active communities and approximately 130 million daily active unique visitors.

What you will do

• Own forecasting and scenario-modeling projects covering campaign delivery, reach, performance, investment tradeoffs, and alternative budgets, bids, audiences, and objectives.
• Connect advertising inventory, demand, audience activity, marketplace competition, and predicted response to estimate achievable campaign outcomes.
• Develop approaches for sparse segments, cold start, seasonality, delayed feedback, and changing marketplace conditions.
• Evaluate accuracy, calibration, uncertainty, cohort performance, and the limits of scenario comparisons; document assumptions and limitations.
• Compare predictions with mature outcomes, investigate systematic errors, and improve forecasts through experiments and observed results.
• Own model training, inference, monitoring, deployment, and iteration while collaborating with Product, Data Science, Ads Delivery, Audience, and Creative teams and mentoring engineers.

Requirements

• Independently designed, shipped, and improved predictive ML systems in advertising, marketplaces, recommendations, search, forecasting, or similarly complex domains.
• Strong foundations in statistical learning, probability, and optimization, with experience using large-scale behavioral or transactional data.
• Practical experience in forecasting, response prediction, probabilistic modeling, multitask learning, or transfer learning.
• Sound evaluation judgment, including temporal validation, segment-level analysis, calibration, uncertainty, and prediction limits under changed conditions.
• Experience addressing sparse observations, cold start, seasonality, distribution shift, selection bias, or delayed labels.
• Strong programming and software engineering skills, including production ML pipelines and services.
• Ability to turn ambiguous product questions into technical plans, lead projects through rollout, and collaborate across functions.

Nice to have

• Demand, supply, inventory, traffic, retail, or capacity forecasting, including time-series methods, hierarchical or global models, and multi-horizon prediction.
• Auction simulation or replay, win-rate and price prediction, bid or budget response curves, or constrained optimization.
• Counterfactual or off-policy evaluation, sensitivity analysis, uncertainty propagation, or combined predictive models for campaign outcomes.
• Population and overlap estimation, reach and frequency models, sampling correction, or saturation modeling.
• Quantile or distributional prediction, calibrated conversion or value prediction, or delayed-feedback modeling.

Culture & Benefits

• Remote employment for US-based employees with comprehensive healthcare and income replacement programs.
• 401(k) with employer match, flexible vacation, paid volunteer time, and generous paid parental leave.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Global benefits supporting workspace, professional development, and caregiving.
• Employment may include restricted stock units and, depending on the position, commission.

Hiring process

• Some interviews may be recorded, transcribed, and summarized by AI; candidates can opt out before scheduled interviews.
• Interview recordings and related personal information are used to evaluate the application and recordings are deleted promptly after a hiring decision.