Research Engineer - Causal AI
Alembic · San Francisco HQ
About this role
## Research Engineer - Causal AI ### About Alembic Alembic is where top engineers solve marketing’s hardest problem: proving what actually works. This is an applied science environment focused on building trusted systems that Fortune 100 companies use to make multimillion-dollar decisions. ### About the Role You’ll solve hard mathematical problems in marketing attribution through both algorithmic innovation and production-quality implementation. You’ll design novel measurement approaches, implement them as production systems, and work directly with customers to ensure statistical rigor at enterprise scale. ### What You’ll Do - Design and implement novel approaches to marketing measurement problems, shipping working code - Build production systems for causal inference that maintain statistical rigor at enterprise scale - Develop algorithms that are mathematically sound and computationally efficient - Collaborate with customers to understand measurement challenges and develop technical solutions - Create tools and libraries that enable internal teams and customers to leverage advanced analytics - Document research and implementation decisions for reproducibility and knowledge transfer ### What Will Help You Succeed **Applied Science & Engineering** - 5+ years developing and shipping research code in production environments - Strong mathematical background (statistics, probability, optimization, causal inference) - Proficient Python developer (production-quality code, not just notebooks) - Causal inference expertise with practical experience applying causal methods to real problems - Data-intensive systems experience processing and analyzing large datasets - Track record of turning research ideas into shipping features - Communication skills to explain complex technical concepts to varied audiences **Domain & Advanced Skills** - MS or PhD with significant applied research experience - Background in econometrics, statistics, or computational social science - Experience in marketing analytics, A/B testing, or measurement domains - Understanding of ML engineering and MLOps practices - Ability to work directly with customers on technical problems - Experience with both Bayesian and frequentist statistical methods **Nice to Haves** - Published applied research or technical writing - Experience in consulting or customer-facing technical roles - Background in operations research or decision sciences - Familiarity with GPU computing and performance optimization - Understanding of privacy-preserving analytics and differential privacy ### Why You Might Be Excited About Alembic - **Hard problems with real impact:** marketing analytics systems influencing multimillion-dollar decisions - **Technical autonomy:** ownership over technical decisions - **Cutting-edge technology:** advanced AI/ML, private NVIDIA DGX clusters, and large-scale data processing - **Elite team:** high-impact work with top engineers - **Startup upside:** early-stage equity with experienced leadership and proven product-market fit ### Why You Might Not Be Excited - If you only want to direct what to build (rather than building and coding alongside the team) - If you prefer fully built-out, static processes for every detail - If you prefer static roles—projects and priorities will adapt to your skills and goals
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.