{"id":3480837,"url":"https://alion.io/job/reddit-staff-machine-learning-engineer-ads-forecasting-scenarios","title":"Staff Machine Learning Engineer, Ads Forecasting & Scenarios","company":{"id":16,"name":"Reddit","domain":"reddit.com","url":"https://alion.io/company/reddit","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":26,"ghost_share":0,"stale_share":0.654,"repost_share":0,"time_to_fill_p50_days":67,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":230000,"max":322000,"currency":"USD","period":"year","gross":null,"usd_annual":322000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Transfer Learning","optional":false},{"name":"Mixture of Experts","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-10-29T15:24:59Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-03T08:42:52Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.\nThe opportunity\nBuild the machine learning capabilities that help advertisers understand what they could achieve on Reddit and make better investment decisions.\nYou will lead models that estimate how campaign outcomes could change with different budgets, bids, audiences, creative performance, or objectives. The work connects supply and demand forecasting, audience availability, response prediction, and marketplace simulation to help advertisers compare alternatives and recognize valuable opportunities they may be missing.\nThis is a hands-on technical leadership role with ownership of modeling direction, evaluation standards, and reusable production capabilities across advertiser planning and recommendations.\nWhat you’ll do\nLead 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.\nConnect inventory, demand, and response. Combine forecasts of available advertising opportunities, audience activity, marketplace competition, and predicted response to estimate achievable delivery and performance.\nEstimate 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.\nQuantify 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.\nBuild 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.\nEstablish trustworthy comparisons. Evaluate numerical accuracy, calibration, uncertainty, and cohort-level performance. Define supported scenarios and identify when additional evidence or experimentation is needed.\nClose the learning loop. Compare recorded predictions with mature outcomes, diagnose systematic errors, and validate scenario estimates through experiments and observed results.\nOwn 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.\nWhat we’re looking for\nA track record of developing and shipping predictive ML systems in advertising, marketplaces, recommendations, search, demand forecasting, or similarly complex domains.\nStrong foundations in statistical learning, probability, and optimization, with experience modeling large-scale behavioral or transactional data.\nDepth in one or more relevant areas: probabilistic or hierarchical forecasting, calibrated conversion/value prediction, multitask or transfer learning, delayed-feedback or survival modeling, or response modeling.\nStrong judgment in evaluation, including temporal validation, calibration, segment-level performance, and the assumptions required to estimate outcomes under changed conditions.\nExperience addressing sparse observations, cold start, seasonality, distribution shift, selection bias, or partially observed labels.\nStrong programming and software engineering skills, including experience building and operating production ML systems.\nDemonstrated ability to lead ambiguous technical initiatives, make practical tradeoffs, and develop other engineers.\nPreferred experience\nComplementary depth in one or more of:\nDemand, supply, and inventory forecasting: Advertising inventory, marketplace demand, traffic, retail demand, or capacity forecasting. Relevant methods include probabilistic time-series models, hierarchical/global forecasting, external-signal modeling, and multi-horizon prediction.\nAuction and investment modeling: Auction simulation or replay, conditional win-rate and price models, bid/budget response curves, or constrained optimization.\nScenario evaluation: Counterfactual or off-policy evaluation, sensitivity analysis, uncertainty propagation, or composition of multiple predictive models.\nReach and audience estimation: Population and overlap estimation, probabilistic reach/frequency models, sampling correction, or saturation modeling.\nAdvanced predictive methods: Mixture-of-experts, distributional or quantile prediction, temporal sequence models, or state-space models.\nWhat success looks like\nAccurate 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.\nBenefits:\nComprehensive Healthcare Benefits and Income Replacement Programs\n401k with Employer Match\nGlobal Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\nFamily Planning Support\nGender-Affirming Care\nMental Health & Coaching Benefits\nFlexible Vacation & Paid Volunteer Time Off\nGenerous Paid Parental Leave \nPay Transparency:\nThis job posting may span more than one career level.\nIn addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.\nTo provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.\nThe base salary range for this position is:\n$230,000—$322,000 USD\nIn select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.\nDuring the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.\nReddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. 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Docs: https://alion.io/developers"}}