About Stripe 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. About The Team The Supportability Evaluation team acts as stewards of the financial ecosystem. Our mission is to protect Stripe’s reputation with our global financial partners by architecting highly precise, automated supportability controls. We develop the AI/ML models and systems that detect and action supportability violations in real‑time. We're responsible for building high‑fidelity detection engines that ensure our merchants remain compliant across the globe, balancing the scale of millions of users with the surgical precision required by the world’s largest financial institutions. What you’ll do As a Machine Learning Engineer in Supportability, you will design, build, train, evaluate, deploy, and own AI/ML models in production, working closely with software engineers, product managers, data scientists, and other machine learning engineers to operate Stripe’s ML‑powered systems, features, and products. You will also have the opportunity to contribute to and influence AI/ML architecture at Stripe and be part of a larger community. Responsibilities Design state‑of‑the‑art AI/ML models and large‑scale systems for detection and decision‑making for Stripe products based on AI/ML principles, domain knowledge, and engineering constraints. Drive the expansion of Stripe’s largest LLM‑based system, scaling its usage and integrating new capabilities through agentic approaches or supervised learning. Rapidly prototype new AI/ML‑based approaches to achieve key business goals. Develop processes to train and evaluate models in offline and online environments. Integrate 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 AI/ML and take calculated risks in transforming innovative ideas into productionized solutions. Explore cutting‑edge AI/ML techniques and evaluate their potential to solve business problems. Who you are We are looking for ML engineers who are passionate about building AI/ML and AI systems that touch the lives of millions. You have experience building and evaluating advanced AI/ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias toward action, and thrive in a collaborative environment. Minimum Requirements 2+ years of industry experience building and shipping AI/ML systems in production. Proficient with AI/ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, and Spark. Knowledge of various AI/ML algorithms and model architectures. Hands‑on experience in designing, training, and evaluating machine learning models. Hands‑on experience in productionizing and deploying models at scale. Experience rigorously evaluating model performance, including cleaning data and working with data‑generating processes to improve signal and reduce noise in high‑noise datasets. Proficiency in creatively applying modern machine learning techniques and Generative AI models to solve complex business problems. Preferred Qualifications MS/PhD degree in AI/ML or related field (e.g., math, physics, statistics). Experience with DNNs including the latest architectures such as transformers and LLMs. Experience working in Java or Ruby codebases. Proven track record of building and deploying AI/ML systems that have effectively solved ambiguous business problems. Experience with online experimentation such as A/B testing or multi‑armed bandits. Experience with model calibration. In‑office expectations Office‑assigned Stripes in most locations are expected to spend at least 50% of the month in their local office. This expectation may vary depending on role, team, and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico; Bengaluru, India; and Dublin, Ireland work 100% from the office. Some teams have greater in‑office attendance requirements, which the hiring manager will discuss. This approach balances in‑person collaboration with flexibility. Pay and benefits The annual salary range for this role in the primary location is CA$162,300‑CA$243,500. This range may change if you are hired in another location. For sales roles, the range provided is the role’s On‑Target Earnings (“OTE”) range, meaning it includes both the sales commissions/bonuses and annual base salary. The salary range may be inclusive of several career levels and will be narrowed during the interview process based on factors such as experience, qualifications, and location. Applicants not located in the primary location may request the annual salary range for their location during the interview. Specific benefits and details about compensation will vary by location and can be discussed in more detail during the interview. Benefits may include equity, company bonus, sales commissions/bonuses, retirement plans, health benefits, and wellness stipends. #J-18808-Ljbffr