Staff Machine Learning Engineer (Pricing)
Core
Design, develop, and deploy machine learning systems for pricing and monetization programs, including donation yield optimization, donor LTV optimization, and fundraising goal suggestions.
Role type
Staff Machine Learning Engineer (Pricing)
Builds
Production ML systems for personalized donation experiences, checkout optimization, and recurring donor management.
Domain
Non-profit fundraising / Monetization
Deliverable
production ML models
Required skills
End-to-end ML system ownership, Python, PyTorch/TensorFlow/Scikit-learn, backend model pipelines, real-time inference, Kubernetes, SQL/Spark/Databricks, causal inference, uplift modeling, A/B testing design, ML observability, stakeholder partnership, technical mentoring
Preferred skills
Pricing/monetization domain expertise, constrained optimization, multi-objective tradeoffs, advanced degree (Master's/Ph.D.)
Technologies
Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, GitHub
Responsibilities
Own end-to-end ML systems for pricing optimization from problem framing to production launch; Design and implement backend model pipelines including feature engineering and evaluation; Build low-latency real-time inferencing services; Develop optimization approaches for pricing-like problems; Establish ML operational excellence with monitoring and incident response; Mentor engineers and set technical direction for ML systems.
Seniority
Staff, hands-on IC with mentorship responsibilities