Role Description & Responsibilities
Machine Learning
About Stripe
Stripe is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Machine Learning role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
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.
Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team’s work from this recent talk .
Key Responsibilities & Day-to-Day Scope
- ✓ How do we evaluate a system offline & online?
- ✓ How do we improve performance to match (and beat) humans?
- ✓ How do we ensure model quality doesn’t degrade online?
- ✓ Does fine-tuning an LLM give us better performance?
- ✓ What are the right OSS and in-house platforms we should invest in?
- ✓ Develop pipelines and automated processes to train and evaluate models in offline and online environments
- ✓ Integrate ML models into production systems and ensure their scalability and reliability
- ✓ Collaborate with product and strategy partners to propose, prioritize, and implement new product features
- ✓ Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions
Official Qualifications & Technical Requirements
- • Have at least 3 years of experience shipping ML systems in production
- • Hold yourself and others to a high bar when working with production systems
- • Take pride in taking ownership and driving projects to business impact
- • Thrive in a collaborative environment
- • 5+ years of experience in full time software development roles
- • Experience shipping LLM integrations to user products with high quality
- • Experience operating in highly ambiguous environments
- • Knowledge about driving a hypothesis from data
Preferred Skills & Technology Stack
- + Familiarity with MLOps pipelines (Docker, Kubernetes, Kubeflow, Triton Inference Server).
- + Knowledge of distributed training techniques and GPU acceleration (CUDA).
- + Relevant coursework, research publication, or open-source contribution in ML/DL.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Stripe
Verified EmployerStripe champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.