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GoFundMe

Online crowdfunding platform for personal campaigns

Manager, Machine Learning Engineering - ML and AI Operations

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 7 years of hands-on experience building and shipping production machine learning systems, including ownership of backend services and machine learning pipelines in a high-availability environment.
  • At least 1 year of experience directly managing engineers, ideally in an MLOps, ML platform, or infrastructure context, with a track record of hiring and developing teams.
  • Strong proficiency in Python and machine learning libraries and frameworks such as PyTorch, TensorFlow, and Scikit-learn, plus software engineering fundamentals including testing, code review, continuous integration and delivery, API design, performance, and reliability.
  • Experience designing and operating real-time model serving at scale, including containerization, scalable inference, feature retrieval, and safe rollout strategies such as canaries, shadowing, and backward-compatible schema evolution.
  • Strong data engineering fluency, including building reliable datasets and features using SQL, Spark/Databricks, and warehouse technologies such as Snowflake, with understanding of event semantics, identity resolution, and data quality controls.
  • Experience implementing machine learning monitoring for technical and business metrics, including drift, calibration, segment performance, latency, and error budgets, and running models reliably in production.
  • Ability to break down ambiguous, high-impact problems, define clear interfaces and success metrics, and deliver iteratively while managing stakeholder expectations across engineering leadership, product, and data science.
  • Strong leadership and mentoring skills, with the ability to raise standards for architecture, engineering quality, and operational rigor for production machine learning and AI systems.

Responsibilities

  • Own the reliability, scalability, and operational health of production machine learning and AI systems across GoFundMe, including training pipelines, feature stores, model serving, and monitoring and observability infrastructure.
  • Lead, hire, and grow a team of machine learning and AI operations engineers, setting technical direction through design reviews, architecture decisions, and shared best practices for production systems.
  • Partner with data science and machine learning engineering teams to streamline model development through production deployment, including machine learning continuous integration and delivery, model packaging, versioning, and rollback strategies.
  • Establish organization-wide machine learning operational standards for model observability, including latency, errors, drift, calibration, and business KPI changes; automated retraining triggers; and incident response playbooks.
  • Build and mature on-call processes, service-level objectives and agreements, and postmortem practices for machine learning and AI systems.
  • Drive operational strategy for generative AI systems alongside traditional machine learning, balancing innovation velocity with safety, compliance, cost, and reliability.
  • Collaborate with Product, Engineering, Design, and Legal/Privacy stakeholders to translate business goals into team priorities and measurable operational outcomes.
  • Manage vendor and platform relationships, including cloud machine learning platforms and large language model providers, and make build-versus-buy decisions that balance cost, control, and speed.
  • Report team health, system reliability metrics, and operational risk to senior engineering leadership.
  • Use tools and platforms including Python, AWS, Databricks, Docker, Kubernetes, Terraform, Snowflake, and GitHub to guide development, deployment, and maintenance of scalable machine learning systems.

Desired Qualifications

  • Familiarity with generative AI and large language model infrastructure and operational considerations, including latency, cost, and safety guardrails.
  • An advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Data Science, or a related technical field.

About the Company

GoFundMe

Online crowdfunding platform for personal campaigns

GoFundMe is an online fundraising platform that helps individuals and organizations raise money for a wide range of needs and dreams, such as medical emergencies, memorial funds, education, and nonprofit support. Users start a fundraiser in about five minutes, tell their story, and share a link to collect donations from their network and beyond. Contributions are made through a secure online payment system, and GoFundMe earns revenue mainly from voluntary donor tips and a small transaction fee on each donation. The platform emphasizes safety and ease of use to ensure a positive experience for both donors and recipients. Compared with others, GoFundMe has built a global community of tens of millions of people and hundreds of millions of donations, which helps campaigns reach a larger audience. Its main goal is to mobilize communities to provide financial assistance and support when people need it most.

Company size
1,001-5,000
Company stage
Series A
Total funding
$1.2B
Headquarters
San Diego, CA
Founded
2010

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