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Senior Staff Machine Learning Engineer - Architect

Senior Staff Machine Learning Engineer - Architect

GoFundMeSan Francisco, CA, United States
1 day ago
Job type
  • Full-time
Job description

Senior Staff Machine Learning Engineer - Architect

GoFundMe is the world's most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causesfor themselves and each other. Together, our community has raised more than $40 billion since 2010.

Join us! The GoFundMe team is searching for our next Senior Staff Machine Learning Engineer to help design our AI platform and develop our next generation of machine learning and AI-based services. You will collaborate with an accomplished and motivated team of individuals to deliver high-impact solutions for our users and our business.

Candidates considered for this role will be located in the San Francisco, Bay Area. There will be an in-office requirement of 3x a week.

The Job :

  • Design and implement AI platforms to enable scalable and secure access to LLMs from multiple model providers for diverse use cases.
  • Design and implement agentic workflows, agentic tool ecosystems, and LLM prompt management solutions.
  • Design, build, and optimize scalable model training, fine tuning, and inference pipelines, ensuring robust integration with production systems.
  • Influence technical strategy and approach to developing embedding stores, vector databases, and other reusable assets.
  • Lead initiatives to streamline ML and AI workflows, improve operational efficiency, and establish standardized procedures to achieve consistent, high-quality results across our AI systems.
  • Design and develop backend services and RESTful APIs using Python and FastAPI, integrating seamlessly with ML pipelines and services.
  • Take operational responsibility for team-owned services, including performance monitoring, optimization, troubleshooting, and participation in an on-call rotation.
  • Collaborate with both technical and non-technical colleagues, including data and applied scientists, software engineers, product managers, and business stakeholders, to deliver reliable and scalable ML-driven products.
  • Coach and mentor fellow ML engineers, promoting a culture of collaboration, continuous improvement, and engineering excellence within the team.
  • Employ a diverse set of tools and platforms including Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, Coralogix, and GitHub to build, deploy, and maintain scalable, highly available machine learning infrastructure.

You :

  • Have 9+ years of hands-on experience in machine learning engineering, AI development, software engineering, or related fields, emphasizing secure, large-scale, distributed system design, AI / ML pipeline development, and implementation.
  • Possess extensive experience designing, developing, and operating scalable backend systems, applying software engineering best practices such as domain-driven design, event-driven architectures, and microservices.
  • Have deep expertise in agentic workflows, AI evaluation solutions, prompt management, and secure AI development and testing practices.
  • Demonstrate strong knowledge of relational and document-based databases, data storage paradigms, and efficient RESTful API design.
  • Possess experience establishing robust CI / CD pipelines, automated testing (unit and integration), and deployment practices.
  • Exhibit strong leadership skills, including effective planning and management of complex projects, mentoring of team members, and fostering a collaborative, high-performing engineering culture.
  • Are an excellent communicator, able to articulate complex technical concepts clearly to both technical and non-technical stakeholders.
  • Have a Bachelor's degree in Computer Science, Software Engineering, or a related technical field (preferred).
  • Are proficient in Python and provisioning cloud-based infrastructure via code (AWS preferred).
  • Sense of humor is optional but appreciated.
  • Why you'll love it here :

  • Make an Impact : Be part of a mission-driven organization making a positive difference in millions of lives every year.
  • Innovative Environment : Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.
  • Collaborative Team : Join a fun and collaborative team that works hard and celebrates success together.
  • Competitive Benefits : Enjoy competitive pay and comprehensive healthcare benefits.
  • Holistic Support : Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
  • Growth Opportunities : Participate in learning, development, and recognition programs to help you thrive and grow.
  • Commitment to DEI : Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.
  • Community Engagement : Make a difference through our volunteering and Gives Back programs.
  • We live by our core values : impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!

    GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences. We do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.

    The total annual salary for this full-time position is $216,500 - $324,500 + equity + benefits. As this is a hybrid position, the salary range was determined by role, level, and possible location across the US. Individual pay is determined by work location and additional factors including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range based on your location during the hiring process.

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