Stripe의 Applied ML 팀에서 제품의 가치를 높일 머신러닝 엔지니어를 채용합니다. 3년 이상의 프로덕션 ML 시스템 구축 경험이 필수이며, LLM을 활용한 모델 학습 및 배포를 주도합니다. 데이터 기반의 가설 검증과 엔드투엔드 프로덕션 배포 역량을 갖춘 분을 찾습니다. 기술적 도전과 비즈니스 임팩트를 동시에 경험할 수 있는 기회입니다.
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.
As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community.
Our team operates fluidly and here are some problems you may tackle:
And in the process you will:
We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action.
