3 months ago
Responsibilities
- Design state-of-the-art machine learning models and large-scale ML systems for underwriting and portfolio management.
- Design systems that accelerate the process from model ideation to deployment.
- Experiment and iterate on models using tools such as PyTorch and TensorFlow.
- Develop pipelines and automated processes for offline and online model training and evaluation.
- Integrate models into production systems and ensure scalability and reliability.
- Collaborate with product and strategy partners to propose, prioritize, and implement product features.
- Evaluate and productionize emerging machine learning and artificial intelligence ideas.
- Contribute to and influence Stripe’s machine learning architecture and broader ML community.
Requirements
- At least 5 years of industry experience building and shipping machine learning systems in production.
- Proficiency with PyTorch, TensorFlow, XGBoost, and Spark.
- Knowledge of machine learning algorithms and model architectures.
- Hands-on experience designing, training, and evaluating machine learning models.
- Hands-on experience productionizing and deploying models at scale.
- Hands-on experience orchestrating complex data pipelines and leveraging large-scale datasets.
- Experience collaborating across teams, particularly with Data Science and Risk Management.
- Preferred: MS or PhD in machine learning, artificial intelligence, mathematics, physics, statistics, or a related field.
- Preferred: Proven track record solving ambiguous business problems with deployed ML systems.
- Preferred: Experience in adversarial domains such as lending, trading, or fraud.
- Preferred: Deep learning experience, including transformers, test-time compute, and reinforcement learning.
Tech Stack
Categories
About Stripe
Stripe builds programmable financial services. 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. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet.