ML Infra Engineer: Build Scalable ML Services & MLOps

Stripe; United States; Hybrid; CAD 172,000 - 258,000; Full time

Benefits offered by this job

Equity

Retirement plans

Health benefits

Wellness stipends

Job summary

Stripe seeks a skilled ML Infra Engineer to build scalable, reliable ML services across notebooks, training, experimentation, serving, and LLM products. You will collaborate with ML engineers and product teams to accelerate delivery and improve productivity.

You will work across regions, own critical tooling, and help transition experiments into production with pragmatic, robust solutions. Hybrid work model offered.

Qualifications

• 2+ years of professional software development with service-oriented architecture and large-scale distributed systems.
• Experience across the full software development lifecycle from user discussions to production deployment.
• Experience on production ML platforms, MLOps solutions, or building LLM applications.
• Experience running operations for high availability, low latency systems.
• Experience partnering with other teams to drive business outcomes.
• A pragmatic approach: knowing when to aim for ideal vs. practical solutions.

Responsibilities

• Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions.
• Creating services and libraries that enable ML engineers to move from experimentation to production across Stripe’s systems.
• Working with product teams and ML engineers to improve day-to-day productivity.
• Taking ownership of and solving technical and product challenges across diverse systems and technologies.

Skills

Service oriented architecture

Large-scale distributed systems

Full software development lifecycle

Production ML platforms

MLOps

LLM applications

High availability

Low latency systems

Cross-team collaboration

Tools

LLM Frameworks

AI agents tooling

Job description

Stripe seeks a skilled ML Infra Engineer to build scalable, reliable ML services across notebooks, training, experimentation, serving, and LLM products. You will collaborate with ML engineers and product teams to accelerate delivery and improve productivity.

You will work across regions, own critical tooling, and help transition experiments into production with pragmatic, robust solutions. Hybrid work model offered.