Staff Machine Learning Engineer

2 Months ago • 7 Years + • Research Development

Job Summary

Job Description

The Staff ML Engineer will design and implement machine learning and AI-based services. Responsibilities include architecting and implementing high-throughput batch inference solutions, designing and optimizing scalable machine learning pipelines, leading initiatives to streamline ML workflows, developing and maintaining backend services, taking operational responsibility for services, and collaborating with various teams to deliver reliable ML-driven products. The engineer will also mentor fellow engineers. The job requires a candidate to be located in Buenos Aires, Argentina.
Must have:
  • 7+ years of experience in machine learning engineering.
  • Experience in architecting and operating scalable backend systems.
  • Deep expertise in containerization technologies (Docker, Kubernetes).
  • Strong knowledge of relational and document-based databases.
  • Experience designing and deploying end-to-end ML systems.
  • Experience establishing robust CI/CD pipelines.
Good to have:
  • Bachelor's degree in Computer Science or related field.
  • Proficiency in Kotlin and Java is preferred.
Perks:
  • Be a part of a mission-driven organization.
  • Collaborate with a diverse, passionate, and talented team.
  • Be part of a fun, supportive team.
  • Live by the core values.

Job Details

Want to help us, help others? We’re hiring! 

GoFundMe is a global community of over 150 million people who come together every day with the common purpose of helping one another. Our mission is to help people help each other through our best in class technology. In 2022, GoFundMe joined together with Classy, a leading nonprofit fundraising software company that enables nonprofits to connect supporters with the causes they care about. Together, we have empowered people and organizations to raise more than $30 billion since 2010. Our vision is to become the most helpful place in the world.

Join us! The GoFundMe team is searching for our next Staff ML Engineer to help design and implement 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.

This is a hybrid position. Candidates considered for this role will be located in Buenos Aires, Argentina.

 

The Job…

  • Architect and implement high-throughput batch inference solutions and distributed, low-latency real-time inference services to support diverse ML applications.
  • Design, build, and optimize scalable machine learning training and inference pipelines, ensuring robust integration with existing production systems.
  • Lead initiatives to streamline ML workflows, improve operational efficiency, and establish standardized procedures to achieve consistent, high-quality results across our ML systems.
  • Develop and maintain 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, New Relic, and GitHub to build, deploy, and maintain scalable, highly available machine learning infrastructure.

You…

  • Have 7+ years of hands-on experience in machine learning engineering, software engineering, or related fields, emphasizing large-scale, distributed system design, ML pipeline development, and implementation.
  • Possess extensive experience architecting, 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 containerization technologies (Docker, Kubernetes, Helm) and proven experience optimizing and deploying containerized workloads in cloud environments.
  • Demonstrate strong knowledge of relational and document-based databases, data storage paradigms, and efficient RESTful API design.
  • Have experience designing, developing, and deploying end-to-end machine learning systems, including data pipelines, model training and serving, and monitoring solutions.
  • 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; additional proficiency in Kotlin and Java is preferred.
  • Sense of humor is optional but appreciated.

 

Why you’ll love it here...

  • Be a part of a mission-driven organization that positively impacts tens of millions of lives every year.
  • Be a Leader in a high-impact product organization and drive business transformation through product.
  • Collaborate with a diverse, passionate, and talented team in a fast-paced and innovative environment.
  • You’ll be a part of a fun, supportive team that works hard and celebrates accomplishments together.
  • We live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose.

GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences. We are committed to providing diversity, equity, and inclusion training to all employees, and 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.

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

Dedication to Diversity 

GoFundMe and Classy are committed to leveraging Diversity, Equity, Inclusion, and Belonging to cultivate a culture that embraces and supports the unique identities, experiences, and perspectives of our people and customers.

Our diversity recruiting priority is recognized under our first DEIB Driver: Opportunity Foster Diversity - we identify, recruit, and invest in top talent- ensure our people reflect the unique identities, experiences, and perspectives of the communities we serve and are all given the chance to grow.

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. 

Learn more about GoFundMe:

We’re proud to partner with GoFundMe.org, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their FY ‘24 annual report.

Our annual “Year in Help” report reflects our community’s impact in advancing our mission of helping people help each other.

For recent company news and announcements, visit our Newsroom.

 

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About The Company

United States (Remote)

United States (Remote)

Buenos Aires, Buenos Aires, Argentina (Hybrid)

Buenos Aires, Buenos Aires, Argentina (Hybrid)

Buenos Aires, Buenos Aires, Argentina (Hybrid)

San Francisco, California, United States (On-Site)

Buenos Aires, Buenos Aires, Argentina (On-Site)

San Francisco, California, United States (Hybrid)

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