Description
As a machine learning engineer for Stripe Capital, you will design, build, train, evaluate, deploy, and own ML models in production with the goals of providing financing opportunities to as many users as possible while satisfying financial performance goals.
You will work closely with software engineers, data scientists, product managers, and risk managers to operate Stripe's ML powered systems, features, and products. You will also contribute to and influence ML architecture at Stripe and be a part of a larger ML community.
Responsibilities include:
- Design state-of-the-art ML models and large scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints
- Design systems to speed up the time from idea to deployment of new models
- Experiment and iterate on ML models (using tools such as PyTorch and TensorFlow) to achieve key business goals and drive efficiency
- 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
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.