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Machine Learning Engineer, Capital Underwriting

1 hour, 37 minutes ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Spark Deep Learning LLM Machine Learning PyTorch Reinforcement Learning TensorFlow Transformers XGBoost
Apply Now
Stripe

Stripe

Stripe is a global technology company that provides financial infrastructure for the internet. They offer a suite of APIs and tools for businesses to accept online and in-person payments, automate financial processes, and embed financial services in th...

Diversified Financial Services
5K-10K
Founded 2009
$8700M raised
View All Jobs 190

Description

  • Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management.
  • Build systems that reduce the time from idea to deployment for new models.
  • Experiment with and iterate on ML models using tools such as PyTorch and TensorFlow.
  • Develop pipelines and automated processes to train and evaluate models in offline and online environments.
  • Integrate ML models into production systems and ensure scalability and reliability.
  • Collaborate with product and strategy partners to propose, prioritize, and implement new features.
  • Work closely with software engineers, data scientists, product managers, and risk managers on ML-powered systems and products.
  • Contribute to and influence ML architecture across Stripe.
  • Engage with new ML and AI developments and turn promising ideas into production solutions.

Requirements

  • 5+ years of industry experience building and shipping ML systems in production.
  • Proficiency with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, and Spark.
  • Knowledge of ML 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 working with large-scale datasets.
  • Experience collaborating across multiple teams, especially Data Science and Risk Management.
  • MS or PhD in ML/AI or a related field such as math, physics, or statistics (preferred).
  • Proven track record of building and deploying ML systems that solve ambiguous business problems (preferred).
  • Experience in adversarial domains such as lending, trading, or fraud (preferred).
  • Experience with deep learning and modern architectures such as transformers, test-time compute, and reinforcement learning (preferred).

Interested in this position?

Apply directly on the company website

Apply Now

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