Staff Software Engineer (AI/ML Platform)

TL;DR

Staff Software Engineer (AI/ML Platform): Leading the technical direction and architecture of next-generation machine learning infrastructure with an accent on scalability, low-latency inference, and LLM orchestration. Focus on driving cross-team initiatives to improve ML development velocity and mentoring engineering teams to build robust, production-grade AI systems.

Location: Must be based in or able to work from South San Francisco or Seattle

Salary: $203,600 - $305,400

Company

Stripe is a global financial infrastructure platform that processes over $1.9T in payments volume annually for millions of businesses.

What you will do

• Define long-term strategy and technical direction for ML infrastructure and platform services.
• Design end-to-end architectures for complex ML workflows, including model training, serving, and feature computation.
• Lead cross-functional initiatives to improve MLOps maturity and development velocity across the organization.
• Arbitrate critical technical decisions balancing reliability, latency, cost, and security constraints.
• Collaborate with data scientists and product teams to translate business needs into scalable technical solutions.
• Mentor and grow engineers while serving as a role model for operational excellence.

Requirements

• 10+ years of professional software development experience in service-oriented architecture and large-scale distributed systems.
• Proven track record as a technical lead for multi-team initiatives.
• Experience building and operating production ML platforms (training, serving, or orchestration).
• Strong communication skills for explaining complex concepts to technical and non-technical stakeholders.
• Ability to thrive in ambiguous environments with high autonomy.
• Must be authorized to work in the US and based in South San Francisco or Seattle.

Nice to have

• Experience with distributed ML training systems and accelerator-backed compute.
• Familiarity with LLM application frameworks and agentic AI patterns.
• Experience with cloud-based AI services like SageMaker, Bedrock, or Databricks.
• Passion for open source or self-driven technical initiatives.

Culture & Benefits

• Opportunity to work on infrastructure powering 1.6% of the world's GDP.
• Collaborative environment working with top-tier data scientists and ML engineers.
• Focus on high-impact, large-scale engineering challenges.
• Commitment to technical excellence and long-term platform strategy.