Staff Machine Learning Engineer (Pricing)

About the role

We’re hiring a Staff Machine Learning Engineer (Pricing) to design, develop, and deploy machine learning systems that power pricing and monetization programs across GoFundMe.

Responsibilities

• Own end-to-end ML systems for pricing optimization, from problem framing and metric definition to model development, launch, and iteration in production.
• Design and implement backend model pipelines including feature engineering, training, and evaluation.
• Build low-latency real-time inferencing services, including API design, caching strategies, model packaging, and deployment on Kubernetes.
• Collaborate with teams to develop instrumentation and event pipelines to capture user and campaign activity required for training and evaluation.
• Apply causal and experimental methodologies to measure impact and avoid biased optimization.
• Develop optimization approaches appropriate for pricing-like problems, such as uplift modeling, bandits, constrained optimization, calibration, and multi-objective tradeoffs.
• Establish ML operational excellence by implementing model observability, automated retraining triggers, rollback strategies, and incident response playbooks for pricing systems.
• Partner cross-functionally with Product, Engineering, Design, and Legal/Privacy stakeholders to translate business goals into measurable technical deliverables and ship safely.
• Mentor and set technical direction for other engineers and scientists through design reviews, architecture decisions, and shared best practices for production ML in monetization.

Requirements

7+ years of hands-on experience building and shipping production machine learning systems, with demonstrated ownership of backend services and ML pipelines in a high-availability environment.

Strong proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, Scikit-learn, plus strong software engineering fundamentals (testing, code review, CI/CD, API design, performance, and reliability).

Experience designing and deploying real-time model serving (sub-100ms to low-hundreds ms latency targets), including containerization, scalable inference, feature retrieval, and safe rollout strategies (canaries, shadowing, backward-compatible schema evolution).

Working knowledge of experiment design and causal measurement for monetization systems, including pitfalls such as selection bias, interference, and delayed outcomes; familiarity with uplift modeling, bandits, or constrained optimization is a strong plus.

Experience implementing ML monitoring for both technical and business metrics (drift, calibration, segment performance, latency, error budgets) and operating models in production.

Ability to break down ambiguous, high-impact problems, define crisp interfaces and success metrics, and deliver iteratively with strong stakeholder communication.

Strong leadership and mentoring skills and a proven ability to raise the bar on architecture, engineering quality, and operational rigor for ML-powered pricing systems.

Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, Data Science, or a related technical field is preferred.

Qualifications

Experience in pricing/monetization or growth optimization domains preferred.

Skills

Employ a diverse set of tools and platforms, including Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, and GitHub, to develop, deploy, and maintain scalable and robust machine learning systems.

(Full-stack experience—e.g., integrating with web clients and experimentation frameworks—is a plus.)

Benefits

The annual U.S. salary range for this full-time position is $215,000 - $322,000.

Additionally pay may vary depending on other factors including skills, experience, education, or training.

Your recruiter can share more about the specific total compensation package based on your location during the hiring process.

If you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com.

Global Data Privacy Notice For Job Candidates And Applicants Depending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here.

By submitting your application, you are agreeing to our use and processing of your data as required.