# Machine Learning Engineer, Support Experience

**Company**: Stripe
**Location**: Toronto, Canada
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/stripe/jobs/7813942
**Canonical**: https://yubhub.co/jobs/job_43ed459a-4da

## Description

## 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

## Skills

### Required
- ML/AI
- Backend Engineering
- PyTorch
- TensorFlow
- Python
- Distributed Systems
- Data Science

### Nice to have
- LLM
- Agentic Planning
- Orchestration Architectures
- Post-Training Methods
- Code Generation
- Benchmarks and Evaluations