Machine Learning Engineer, Support Experience · Stripe

Sat, 18 Apr 2026 15:53:43 GMT
Engineering

Stripe · Toronto, Canada · hybrid

Job Role

As a Machine Learning Engineer on the Support Experience team, you'll play a crucial role in enhancing our self-serve support experiences.

About the Team

The Support Experience engineering organization builds and improves Stripe's user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions.

Responsibilities

Design and implement state-of-the-art ML models and large-scale ML systems for enhancing self-serve support capabilities, balancing ML principles, domain knowledge, and engineering constraints

Develop and optimize contextual conversation models and ML-powered resolution flows for common support scenarios, using tools such as PyTorch, TensorFlow, and XGBoost

Create and refine pipelines for training and evaluating models in both offline and online environments, with a focus on improving support quality and user satisfaction

Implement ML features that streamline information collection and processing for support agents, enhancing overall support efficiency

Collaborate with product, strategy, and content teams to propose, prioritize, and implement new AI-driven support features and improve answer capabilities

Requirements

Bachelor's Degree in ML/AI or related field (e.g. math, physics, statistics)

3+ years in AI/ML and backend engineering, including building and operating production ML systems at global scale with stringent SLOs,balancing reliability, latency, and cost,with privacy, security, and compliance by design.

Deep and up-to-date applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration architectures, post-training methods, code generation, benchmarks and evaluations, etc.

Familiarity with classical ML methods and common frameworks e.g. Pytorch, TensorFlow.

Proficient in Python; strong distributed systems and data science fundamentals.

Experience working closely with product management, design, other engineers, and other cross-functional partners.

Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Preferred Qualifications

MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)

Experience working in Java or Ruby codebases

Experience designing, deploying, and owning Agentic LLM solutions (e.g., multi-step orchestrators, tool use/function calling) specifically for complex customer support or internal workflow automation.

Comfortable working with distributed teams across multiple locations and time zones