Research Engineer - Causal AI

About AlembicAlembic is where top engineers are solving marketing's hardest problem: proving what actually works. If you're looking for frontier technical challenges at an applied science company, this is the place.At Alembic, we're not just building software—we're decoding the chaos of modern marketing. Join Alembic to build trusted systems that Fortune 100 companies use to make multimillion-dollar decisions. We're backed by leading tech luminaries including WndrCo (founded by DreamWorks founder Jeffrey Katzenberg), Jensen Huang, Joe Montana, and many more.About the RoleWe're looking for an Applied Scientist who solves hard mathematical problems in marketing attribution through both algorithmic innovation and production-quality implementation. You'll design novel approaches to measurement challenges, implement them as production systems, and work directly with customers to ensure statistical rigor at enterprise scale.This role is ideal for someone who wants to apply deep technical expertise to real-world problems—shipping code that makes a difference, not just publishing papers.What You'll DoDesign and implement novel approaches to marketing measurement problems, shipping working codeBuild production systems for causal inference that maintain statistical rigor at enterprise scaleDevelop algorithms that are both mathematically sound and computationally efficientCollaborate with customers to understand their measurement challenges and develop technical solutionsCreate tools and libraries that enable both internal teams and customers to leverage advanced analyticsDocument research and implementation decisions for reproducibility and knowledge transferWhat Will Help You SucceedApplied Science & Engineering5+ years developing and shipping research code in production environmentsStrong mathematical background - statistics, probability, optimization, causal inferenceProficient Python developer - can write production-quality code, not just notebooksCausal inference expertise - practical experience applying causal methods to real problemsData-intensive systems - experience processing and analyzing large datasetsResearch to production - track record of turning research ideas into shipping featuresCommunication skills - can explain complex technical concepts to varied audiencesDomain & Advanced SkillsMS or PhD with significant applied research experienceBackground in econometrics, statistics, or computational social scienceExperience in marketing analytics, A/B testing, or measurement domainsUnderstanding of ML engineering and MLOps practicesAbility to work directly with customers on technical problemsExperience with both Bayesian and frequentist statistical methodsNice to HavesPublished applied research or technical writingExperience in consulting or customer-facing technical rolesBackground in operations research or decision sciencesFamiliarity with GPU computing and performance optimizationUnderstanding of privacy-preserving analytics and differential privacyWhy You Might Be Excited About AlembicHard problems with real impact: You'll tackle the hardest challenges in marketing analytics while building systems that influence multimillion-dollar decisions at Fortune 100 companiesTechnical autonomy: You want ownership over technical decisions and the freedom to solve complex problems your wayCutting-edge technology: Work with advanced AI/ML algorithms, composite AI solutions, private NVIDIA DGX clusters, and the latest in data processing at scaleElite team: Join top engineers who thrive on challenging problems and high-impact workStartup upside: Early-stage equity opportunity with experienced leadership and proven product-market fitWhy You Might Not Be ExcitedIf you only want to tell people what to build instead of building and coding alongside them, we're not the environment for youYou prefer company practices with 100% built-out process for every detailYou prefer static over dynamic. Projects, priorities, and roles will adapt to your skill set and goals. Though we have real paying customers and a playbook for growth, we proudly remain an early-stage startupCompensation Range: $200K - $250KLocationSan Francisco HQAddressSan Francisco, CaliforniaEmployment TypeFull timeLocation TypeOn-siteDepartmentEngineeringApplied ScienceCompensationIC - SeniorEstimated salary commensurate with experience. $200K – $225K • Offers EquityIC - StaffEstimated salary commensurate with experience. $225K – $250K • Offers EquityTier GuideOur Compensation Philosophy:Market-based: Our formula ensures new hires earn at or above real-time benchmarks. Ownership: Our generous equity program ensures new hires are owners, not just employees.Transparent: We openly discuss salary expectations to avoid surprises later in the process. Data-driven: We use objective data to remove bias and ensure consistency in compensation decisions.