Machine Learning Engineer, Support Experience

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companiesfrom the worlds largest enterprises to the most ambitious startupsuse 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 everyones reach while doing the most important work of your career.

About the team

The Support Experience engineering organization builds and improves Stripes 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. Were accountable for the quality and reliability of this support stack and we use data and firsthand user research to continuously improve it.

Providing great support to users of all sizes is culturally important to everyone at Stripe. We are a group of friendly user-oriented engineers that partner closely with Stripes world-class design product and operational teams. This includes the external-facing support interfaces () content entry points internal tooling case routing and helping product teams across the company reduce support volume by improving our products. We are also using the latest generative AI technologies to re-imagine support experiences and are developing AI assistants for Stripes users and internally to help our operations teams be more productive.

What youll do

As a Machine Learning Engineer on the Support Experience team youll play a crucial role in enhancing our self-serve support experiences. You will be responsible for designing building training evaluating deploying and owning ML models in production. For example we apply LLMs to answer user questions with conversational agents and personalize product documentation and are building automated systems to solve complex user problems. You will work closely with software engineers machine learning engineers product managers and data scientists to operate Stripes ML powered systems features and products. You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community.

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
• Stay current with the latest developments in ML/AI particularly in natural language processing and conversational AI and apply innovative ideas to improve support experiences

Who you are

We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions. You have experience developing efficient feature pipelines building advanced ML models and deploying them to production. You are comfortable with ambiguity love to take initiative have a bias towards action and thrive in a collaborative environment.

Minimum requirements

• Bachelors 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 SLOsbalancing reliability latency and costwith 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