Staff Machine Learning Engineer, Credit Products

Block

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
San Francisco, CA
Salary
$228,700–$343,100 / yr
Posted
122 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $227k
This role $286k
$166k most similar roles pay here $362k

This role pays more than 88% of similar roles. Most pay $197,981–$256,950 — the shaded band above. At the midpoint, this role pays about $286k versus about $227k for comparable roles.

Based on 240 similar postings.

Employer

About Block

Block, Inc. (formerly Square) is a financial technology company operating the Square merchant payments ecosystem, Cash App peer-to-peer payments, TIDAL music streaming, and Bitcoin-focused financial services. Industry: Financial Technology & Payments

Block currently has 53 open roles on FindRole.

Listed pay typically runs $217,800–$326,800 across 52 roles with salary data.

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View all roles at Block

At a glance

TL;DR · Staff Machine Learning Engineer, Credit Products

Careers - Staff Machine Learning Engineer, Credit Products (Square Financial Services) joins the Credit and Lending team to provide predictive intelligence for capital-intensive products. This role involves full-stack ownership of the credit engine, where you will curate novel data signals, implement decisioning logic, and manage the entire lifecycle of credit modeling in production environments. You will build ML infrastructure to scale data ingestion, deploy advanced architectures like neural networks, and use data science techniques to interpret messy datasets for business decisions. The role requires a scientific mindset to improve underwriting capabilities for underserved segments while navigating regulated banking constraints. Key skills include proficiency in tree-based models, gradient boosting, and production-grade software architecture. You must possess strong quantitative intuition and the ability to communicate complex technical findings to non-technical stakeholders within a highly regulated financial framework.

What does a Machine Learning Engineer earn in California?

Median $246394 from 172 postings across 28 companies.

See salary data

What you'll do

  • Evaluate alternative data sources and deploy advanced architectures to improve predictive accuracy for new customer segments.
  • Lead ML operations and infrastructure initiatives to scale data ingestion and support complex neural networks.
  • Design and implement the full credit modeling stack from development through production integration.
  • Apply data science techniques to process messy datasets and provide clarity for business decisions.
  • Identify and execute technical improvements to credit policies to improve outcomes for customers and the bank's portfolio.
  • Troubleshoot issues in real-time production environments and perform scheduled updates to existing models.
  • Balance rapid innovation with the safety, soundness, and compliance requirements of a regulated bank.

What we're looking for

  • Minimum of 8 years experience with a Bachelor's degree; or 6 years with a Master's; or 3 years with a PhD.
  • Degree in a technical field such as Computer Science, Mathematics, Statistics, Physics, or Engineering.
  • Proven track record of developing and deploying machine learning and statistical models in production environments.
  • Strong quantitative intuition and data visualization skills for sophisticated ad-hoc and exploratory analysis.
  • Full-stack proficiency including experience with data pipelines and production-grade software architecture.
  • Ability to communicate complex technical information clearly to both technical and non-technical stakeholders.
  • Experience with tree-based models and gradient boosting is helpful but not required.

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