Remote Job: Staff Site Reliability Engineer – Machine Learning Infrastructure at Wikimedia Foundation

Organization: Wikimedia Foundation
Position: Staff Site Reliability Engineer (Machine Learning Infrastructure)
Location: Remote (across eligible countries in Americas, Europe, and Africa)
Job Type: Full-time
Salary Range (U.S.): $129,347 – $200,824 (adjusted based on location outside the U.S.)

About This Opportunity

The Wikimedia Foundation, the non-profit powering Wikipedia and other free knowledge projects, is seeking a Staff Site Reliability Engineer focused on Machine Learning Infrastructure. This fully remote role is part of a distributed team building robust systems that empower machine learning researchers and engineers to deploy, scale, and monitor models in production.

This is a high-impact opportunity to shape the future of open-access AI tools in one of the most visited websites globally.

Key Responsibilities

• Design, build, and maintain ML infrastructure for training, deployment, and monitoring

• Optimize system performance, availability, and scalability

• Collaborate with ML engineers, researchers, product teams, and volunteer contributors

• Lead infrastructure automation, observability, and monitoring

• Contribute documentation and mentor team members on reliability engineering best practices

• Ensure security, capacity planning, and operational excellence in ML systems

Required Qualifications

• 7+ years in SRE, DevOps, or infrastructure engineering roles

• Hands-on experience with on-premise ML infrastructure: Kubernetes, Docker, GPU acceleration

• Proficiency with automation tools: Terraform, Helm, Ansible, Argo CD

• Monitoring experience with Prometheus, Grafana, ELK Stack, etc.

• Familiarity with ML frameworks like PyTorch, TensorFlow, scikit-learn

• Strong communication skills and ability to work across global, asynchronous teams

Desired Strengths

• Expertise in scaling high-performance ML workloads

• Strong background in system reliability and operational automation

• Commitment to open-source software and decentralized knowledge access

• Experience mentoring and contributing to technical knowledge-sharing

What Wikimedia Offers

• Remote-first work across 40+ countries

• Competitive salary based on location and experience

• Transparent, mission-driven compensation structure

• Inclusive, diverse workplace committed to equity and openness

• Global impact on how billions access knowledge

Apply now to help build the machine learning infrastructure behind one of the world’s most important open knowledge platforms.