Base Salary
$215k - $322k/yr
Responsibilities
- Own end-to-end ML systems for pricing optimization, from problem framing and metric definition through production launch and iteration.
- Design backend model pipelines for feature engineering, training, and evaluation.
- Build low-latency real-time inference services with API design, caching, model packaging, and Kubernetes deployment.
- Develop instrumentation and event pipelines for user and campaign activity while maintaining schema quality, lineage, and privacy by design.
- Apply causal and experimental methods, including A/B testing, guardrail metrics, sequential testing, and counterfactual approaches.
- Develop pricing optimization methods such as uplift modeling, bandits, constrained optimization, calibration, and multi-objective tradeoffs.
- Implement model observability, automated retraining triggers, rollback strategies, and incident response playbooks.
- Partner with Product, Engineering, Design, and Legal/Privacy stakeholders to translate business goals into measurable deliverables.
- Mentor engineers and scientists and set technical direction through design reviews, architecture decisions, and shared production ML practices.
Requirements
- 7+ years of hands-on experience building and shipping production machine learning systems.
- Strong proficiency in Python and ML frameworks including PyTorch, TensorFlow, and Scikit-learn, along with strong software engineering fundamentals.
- Experience designing and deploying real-time model serving with low-latency targets, containerization, scalable inference, feature retrieval, and safe rollout strategies.
- Strong data engineering fluency with SQL, Spark/Databricks, and warehouse technologies such as Snowflake.
- Working knowledge of experiment design and causal measurement for monetization systems; uplift modeling, bandits, or constrained optimization experience is a strong plus.
- Experience implementing monitoring for technical and business ML metrics and operating models in production.
- Ability to define interfaces and success metrics, solve ambiguous high-impact problems, and communicate effectively with stakeholders.
- Strong leadership and mentoring skills with experience raising architecture, engineering quality, and operational rigor.
- Experience in pricing, monetization, or growth optimization is preferred.
- Advanced degree in Computer Science, Statistics, Data Science, or a related technical field is preferred.
Benefits
- Annual full-time U.S. salary range of $215,000-$322,000, plus equity and comprehensive benefits including healthcare, dental, vision, life insurance, and a 401(k) savings program.
- Hybrid work arrangement with an in-office requirement three times per week in the San Francisco Bay Area.
- Financial assistance for hybrid work and family planning, generous parental leave, flexible time off, and mental health and wellness resources.
- Learning, development, recognition, diversity and inclusion, employee resource group, and volunteering programs.
Tech Stack
Categories
About GoFundMe
There are a billion good intentions tucked inside each and every one of us. At GoFundMe, we believe that the impulse to help a person, fix a neighborhood, or change a nation should never be ignored. In fact, it should be shared with the entire world. That’s why we make it easy to inspire the world and turn your compassion into action. By giving people the tools they need to capture and share their story far and wide, we have built a community of more than 200 million donors and helped organizers raise over $15 billion for the causes important to them—and we are just getting started. Check out current job openings, join our team, and be a part of the change below. ## GoFundMe has assembled one of the best management teams in the business to build the next leading consumer Internet company, including leaders from LinkedIn, Groupon, and Google. We are also funded by some of Silicon Valley’s best venture capital firms, including Accel, Greylock, and TCV.