Staff Machine Learning Engineer, Credit Products

Block

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$228,700–$343,100 / yr
Posted
122 days ago
Freshness
Confirmed live yesterday

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.

Most-posted roles

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 advanced architectures to enhance underwriting accuracy, lead ML operations and infrastructure initiatives like scaling data ingestion, and utilize data science techniques to interpret messy datasets for business decisions. The role requires expertise in tree-based models, gradient boosting, and software architecture while navigating the constraints of a regulated bank. You must possess strong quantitative intuition, data visualization skills, and the ability to communicate complex technical concepts to non-technical stakeholders while solving problems related to credit policy and risk management.

What does a Machine Learning Engineer earn in Washington?

Median $241750 from 66 postings across 14 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 optimize portfolio outcomes.
  • Troubleshoot issues in real-time production environments and perform scheduled model updates.
  • Balance rapid innovation with the safety, soundness, and compliance requirements of a regulated bank.

What we're looking for

  • A degree in a technical field such as Computer Science, Mathematics, Statistics, Physics, or Engineering.
  • Minimum of 8 years experience with a Bachelor's degree, 6 years with a Master's, or 3 years with a PhD.
  • Proven experience 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 across the technical stack from data pipelines to production-grade software architecture.
  • Ability to communicate complex information clearly to both technical and non-technical audiences.
  • Experience with tree-based models and gradient boosting is helpful but not required.
  • Ability to balance rapid innovation with the requirements of safety, soundness, and compliance in a regulated bank.

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