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Staff Machine Learning Engineer, Credit Products (Square Financial Services)

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Block

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Location:
United States , Seattle

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Category:
IT - Software Development

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Contract Type:
Employment contract

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Salary:

194500.00 - 343100.00 USD / Year
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Job Description:

The Credit and Lending team is responsible for the predictive intelligence that underpins Block's primary capital-intensive products. These products unlock unique access to credit for our customers, many of whom are otherwise underbanked and underserved by the traditional financial system. As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems. This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block's top-line growth. Our credit products are material drivers of the company's profitability and are frequently highlighted in executive reviews and quarterly earnings reports. We are seeking a scientifically-minded contributor capable of delivering extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques.

Job Responsibility:

  • Apply a rigorous scientific mindset to the challenge of underwriting new customer segments
  • Lead complex ML Operations and Infrastructure initiatives
  • Design and implement the full credit modeling stack
  • Use data science techniques to leverage new data sources for modeling
  • Identify and execute material improvements to credit policy
  • Support team members in ad-hoc and scheduled updates to existing models
  • Operate effectively within the framework of a regulated bank

Requirements:

  • Minimum of 8 years of related experience with a Bachelor's degree
  • or 6 years and a Master's degree
  • or a PhD with 3 years experience, with a focus on developing and deploying machine learning and statistical models in production environments
  • A degree in a technical field (e.g., Computer Science, Mathematics, Statistics, Physics, or Engineering)
  • Strong quantitative intuition and data visualization skills
  • Full-stack proficiency preferred
  • The versatility to communicate clearly with both technical and non-technical audiences
  • A pragmatic approach to problem-solving

Nice to have:

Experience with tree-based models and gradient boosting

What we offer:
  • Remote work
  • medical insurance
  • flexible time off
  • retirement savings plans
  • modern family planning

Additional Information:

Job Posted:
May 15, 2026

Employment Type:
Fulltime
Work Type:
Remote work
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