LaunchDarkly
Staff Engineer, Experimentation
$183K–$295K
Remote - US +1 · Remote · Staff · Full-time · Posted Apr 16, 2026
- Location
- Remote - US
Oakland, California, United States - Experience
- 10+ years building large-scale experimentation platforms, statistical analysis systems, or data-intensive backend services.
About the job
Build and lead the statistical and warehouse-native platform that powers customer experimentation, including adaptive methods such as contextual bandits.
What you'll do
- Build statistically correct experimentation features, including hypothesis testing, sequential analysis, variance reduction, and power analysis.
- Design warehouse-native, warehouse-agnostic analysis and lead adaptive experimentation systems.
- Set technical direction, mentor engineers, collaborate across teams, and own operational excellence, including on-call.
What they ask for
- Applied-statistics knowledge covering experiment design, hypothesis testing, sequential analysis, variance reduction, and power analysis.
- Experience with adaptive experimentation ML, such as contextual bandits, Thompson sampling, Bayesian optimization, or RL-based allocation.
- Experience designing warehouse-agnostic systems and expertise in Go, Python, or similar.
- Experience with event-driven architectures, data pipelines, large-scale data processing, cloud environments (AWS, GCP), and infrastructure-as-code.
Pay
$214,800 - $295,350 USD base salary; $193,400 - $265,870 USD base salary; $182,600 - $251,0202 USD base salary
Tools
Snowflake, Databricks, Redshift, BigQuery, Go, Python, AWS, GCP
AI focus
Develop adaptive experimentation ML systems, including contextual bandits, Bayesian optimization, and automated allocation.
Model-written summary · the original posting is authoritative