Machine Learning Engineering Manager, GoFundMe
$219-329k
+ Equity
3 days a week in office
Social fundraising platform
Be an early applicant
Social fundraising platform
1001+ employees
Be an early applicant
$219-329k
+ Equity
3 days a week in office
1001+ employees
Company mission
To help people fundraise for the personal, business, and charitable causes that matter most to them.
Role
Who you are
- 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
- 1-3+ years of experience directly managing engineers, ideally in an MLOps, ML platform, or infrastructure context, with a track record of hiring and developing strong teams
- 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) — enough depth to stay hands-on and credible with your team
- Experience designing and operating real-time model serving at scale, including containerization, scalable inference, feature retrieval, and safe rollout strategies (canaries, shadowing, backward-compatible schema evolution)
- Strong data engineering fluency: building reliable datasets and features using SQL, Spark/Databricks, and warehouse technologies (e.g., Snowflake), with an understanding of event semantics, identity resolution, and data quality controls
- Proven experience implementing ML monitoring for both technical and business metrics (drift, calibration, segment performance, latency, error budgets) and running models reliably in production
- Familiarity with generative AI/LLM infrastructure and operational considerations (latency, cost, safety guardrails) is a strong plus
- Ability to break down ambiguous, high-impact problems, define crisp interfaces and success metrics, and deliver iteratively while managing stakeholder expectations across engineering leadership, product, and data science
- Strong leadership and mentoring skills and a proven ability to raise the bar on architecture, engineering quality, and operational rigor for production ML/AI systems
- Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, Data Science, or a related technical field is preferred
- Sense of humor is optional but appreciated
What the job involves
- Join GoFundMe as our next Manager, Machine Learning Engineering (ML and AI Operations)
- In this role, you will lead the team responsible for the infrastructure, pipelines, and operational rigor that keep GoFundMe's machine learning and AI systems reliable, scalable, and safe in production
- This role requires strong technical judgment across the ML lifecycle (data → training → online inference → monitoring), a strong understanding of how to enable AI applications to operate safely at scale, and a proven ability to build and lead a high performance team that operates production ML/AI systems with the same rigor as core infrastructure
- Own the reliability, scalability, and operational health of ML/AI production systems across GoFundMe, including training pipelines, feature stores, model serving, and monitoring/observability infrastructure
- Lead, hire, and grow a team of ML/AI operations engineers, setting technical direction through design reviews, architecture decisions, and shared best practices for production ML and AI systems
- Partner with data science and ML engineering teams to streamline the path from model development to production deployment, including CI/CD for ML, model packaging, versioning, and rollback strategies
- Establish ML operational excellence org-wide by driving standards for model observability (latency, errors, drift, calibration, business KPI deltas), automated retraining triggers, and incident response playbooks
- Build and mature on-call processes, SLOs/SLAs, and postmortem practices for ML/AI systems, treating model incidents with the same discipline as production infrastructure incidents
- Drive operational strategy for GoFundMe's generative AI systems alongside traditional ML, balancing innovation velocity with safety, compliance, cost, and reliability
- Collaborate cross-functionally with Product, Engineering, Design, and Legal/Privacy stakeholders to translate business goals into team priorities and measurable operational outcomes
- Manage vendor and platform relationships (e.g., cloud ML platforms, LLM providers) and make build-vs-buy calls that balance cost, control, and speed
- Report on team health, system reliability metrics, and operational risk to senior engineering leadership
- Employ a diverse set of tools and platforms, including Python, AWS, Databricks, Docker, Kubernetes, Terraform, Snowflake, and GitHub, to guide your team in developing, deploying, and maintaining scalable and robust machine learning systems
Our take
One of the most well-known fundraising platforms in the world, GoFundMe makes raising money online exceptionally easy. The platform initially focused on charity and good causes, but its scope has now expanded to include start-up business funding. What makes the platform attractive is its ability to democratise fundraising.
GoFundMe's rapid rise in popularity has been helped by its social media integrations and the speed at which individuals can start funds. With strategic foresight, the company launched its GoFundMe Guarantee in 2016, a pledge to protect donors from fraud or platform misuse - knowing that its continued growth could only be hampered by security issues or donor deception. This guarantee is what has enabled the company to remain the largest crowdfunding platform in the world.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-6% employee growth in 12 months
Company
Company benefits
- Wide range of health insurance options, including medical, dental, and vision (GoFundMe covers 100% of employee premiums, and 80% of spouse and dependents)
- $600 annual fitness and wellness reimbursement
- Weekly massages
- Standing desks
- Fully-stocked kitchens & daily lunches
- Team off-sites & monthly social events
- Many of our offices are dog friendly
- 10 paid holidays, 17 days of accrued vacation per year, unlimited sick time & three volunteer days
- Enhanced parental leaves
- $50/month for employees commuting to and from work (public transit and/or parking)
- Caltrain GoPasses for our Bay Area commuters
- "Gives Back" program, where employees nominate fundraisers weekly for donations from GoFundMe
- Quarterly volunteer events in each office to give back to our local communities
- 401(k) retirement plan with company matching
- Access to learning tools and resources, including a subscription to Udemy, guest speakers, and internal brown bag sessions
Company HQ
Centennial, Redwood City, CA
Leadership
Margaret Richardson
(Chief Marketing & Corporate Affairs Officer)Formerly worked at Airbnb as Vice President of Trust and Director of Global Policy. They worked in Trust & Safety at Apple prior to becoming a Member of Pipeline Angels.
Tim Cadogan
(CEO)CEO since 2020. Previously CEO at OpenX, where they now serve as Chair of the Board. Has also served as Board Director at a number of businesses - they still hold this position at LiveRamp.
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