Stripe
Financial Services
StaffSoftwareEngineer,MachineLearningPlatform
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Software Engineer, Machine Learning Platform at Stripe. Skills: ML Platform, System design, Technical leadership. Take ownership of architecture. Take ownership of system design”
Industry & Context.
Problem-solving
What They're Looking For.
Must Have
10+ years software development experience, Service-oriented architecture experience, Large-scale distributed systems experience, Technical lead experience, Production ML platform services experience, Product instincts, Deep business context understanding, Explain complex technical concepts, Work cross-functionally, Thrive on autonomy, Comfortable in ambiguous environments, Hands on AI tools experience
Nice to Have
Large-scale serving infrastructure experience, Data infrastructure experience for ML, Familiarity with LLMs, Familiarity with LLM frameworks, Familiarity with agentic AI patterns, Rapidly develop prototypes experience, Iterate based on user feedback experience, Familiarity with cloud services, Familiarity with cloud AI/ML services, Experience training ML models, Experience shipping ML models, Synthesize ideas across organization, Setting compelling technical vision, Comfortable with distributed teams, Passion for side-projects, Passion for open source, Passion for self-driven initiatives
What You'll Do.
Take ownership of architecture
Take ownership of system design
Define technical directions
Design system architecture
Turn ideas into solutions
Shape platform roadmap
Shape product roadmap
Translate needs into requirements
Translate needs into solutions
Arbitrate critical decisions
Engage senior leaders
Advise leadership team
Drive cross-team initiatives
Improve MLOps maturity
Design software systems
Implement software systems
Operate software systems
How You'll Work.
Team & Collaboration
Cross-functional teams; Work with product teams; Work with data scientists; Work with platform teams; Engage senior leaders; Advise leadership team
Communication Scope
Explain complex concepts; Advise leadership
Full Job Description
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Stripe processes over $1.9 T in payments volume per year, which is roughly 1.6% of the world's GDP, for millions of customers from startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), we have lots of exciting opportunities to innovate in ML Platform at Stripe. The ML Platform team builds the platforms and services that enable ML engineers and data scientists across Stripe to take the data and build features and models from prototype to production — reliably, at low latency, and at scale. We work closely with product teams, data scientists, and platform infrastructure teams to build powerful, flexible, and user-friendly systems that substantially increase ML velocity across the company. What you’ll do You will serve as a technical lead across the ML Platform space and a key contributor to the evolution of the platforms that power Stripe's ML-driven products. As a Staff Engineer, you'll be empowered to make decisions with a large impact on Stripe. You will influence our investments and strategy while making our systems more reliable, secure, and a delight to use. You will work cross-functionally with other tech staff, data science, product, and senior leadership to land a bigger impact of ML at Stripe. You will help define the long-term strategy and lead the technical
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