Manager, Machine Learning Engineering

Go Fund Me
San Francisco
Workplace: HybridFull timeUSD 219,000 - 329,000 annuallyFunction: Data Science & Machine LearningExperience: 7+ yearsEducation: mastersSkills: ["Leadership","Mentoring","Technical judgment","Cross-functional collaboration","Problem-solving"]

Lead a team responsible for the reliability, scalability, and operational excellence of GoFundMe’s ML/AI production systems. Own the end-to-end operations stack—training pipelines, feature stores, model serving, monitoring/observability, and incident response—while partnering with data science and engineering to streamline deployment via CI/CD and safe rollout practices. Drive generative AI operational strategy and build durable on-call, SLO/SLAs, and postmortem processes.

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FursaFursa
Go Fund Me
Go Fund Me
3 days ago

Manager, Machine Learning Engineering

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Source: Company careers pageValidated by: Fursa AI
Last checked: 20 hours agoStatus: Live

Job Summary

Lead a team responsible for the reliability, scalability, and operational excellence of GoFundMe’s ML/AI production systems. Own the end-to-end operations stack—training pipelines, feature stores, model serving, monitoring/observability, and incident response—while partnering with data science and engineering to streamline deployment via CI/CD and safe rollout practices. Drive generative AI operational strategy and build durable on-call, SLO/SLAs, and postmortem processes.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Manager level

Key Responsibilities

  • •Own the reliability, scalability, and operational health of ML/AI production systems, including training pipelines, feature stores, model serving, and monitoring infrastructure.
  • •Lead, hire, and grow a team of ML/AI operations engineers, setting technical direction through design reviews and architecture decisions.
  • •Partner with data science and ML engineering to streamline model development to production deployment, including CI/CD, packaging, versioning, and rollback.
  • •Establish ML operational excellence org-wide by driving standards for model observability, automated retraining triggers, and incident response playbooks.
  • •Manage on-call processes, SLOs/SLAs, postmortems, and generative AI operational strategy balancing innovation with safety, compliance, cost, and reliability.

Pay and Benefits

Salary: USD 219,000 - 329,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife Insurance401kParental Leave

Key Requirements

  • •7+ years building and shipping production machine learning systems in a high-availability environment.
  • •1-3+ years managing engineers, with experience hiring and developing teams in MLOps, ML platform, or infrastructure contexts.
  • •Strong proficiency in Python and ML libraries/frameworks including PyTorch, TensorFlow, and Scikit-learn, with solid software engineering fundamentals (testing, code review, CI/CD, API design, performance, reliability).
  • •Experience designing and operating real-time model serving at scale, including containerization, scalable inference, feature retrieval, and safe rollout strategies.
  • •Strong data engineering fluency using SQL, Spark/Databricks, and warehouse technologies like Snowflake, plus ML monitoring for technical and business metrics in production.
Experience:7+ yearsMLOpsMachine learningML platformProduction systems
Education:Master's in Computer Science, Statistics, Data Science, or related technical field
Skills:LeadershipMentoringTechnical judgmentCross-functional collaborationProblem-solving
Languages:English
Tech Stack:PythonAWSDatabricksDockerKubernetesTerraformSnowflakeGitHubPyTorchTensorFlowScikit-learnSQLSparkCI/CD

Company Brief

Go Fund Me
Operates an online crowdfunding platform that enables individuals and organizations to raise money for personal causes, medical expenses, charities, and community projects through donations from the public.
Industry: Online Marketplaces
Company Size: Large (251 to 1,000 employees)
Growth: Established Company
Headquarters: San Diego, United States
Founded: 2010
WebsiteLinkedIn