Staff Machine Learning Engineer

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Plano, TXMcLean, VA
Employment: Full-time
Posted: 47 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $231k

$173k $294k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $207,825–$254,750.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Staff Machine Learning Engineer

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The Staff Machine Learning Engineer provides technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale. You will participate in detailed technical designs, develop and review model and application code, and ensure high availability for machine learning applications. Your daily responsibilities include delivering software components that solve challenging business problems in the financial services industry, optimizing data pipelines, and leading large-scale initiatives. You will utilize cloud-based architectures and technologies, including C, C++, Python, or Scala, alongside tools like Dask, RAPIDS, and the PyData ecosystem featuring NumPy, Pandas, and Scikit-learn. This role requires expertise in distributed computing and the full machine learning development lifecycle to build intelligent systems and production-ready data pipelines within a business-critical setting.

What does a Machine Learning Engineer earn?

Median $235750 from 323 postings across 48 companies.

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Skills

Machine Learning Python C++ Scala C Dask RAPIDS NumPy Pandas Scikit-learn Distributed Computing Data Pipelines High Performance Computing

What you'll do

Deliver ML models and software components to solve complex financial services business problems.
Lead the technical design and implementation of production-scale machine learning applications.
Develop and review model and application code to ensure high availability and performance.
Optimize data pipelines to efficiently feed machine learning models.
Leverage cloud-based architectures to deliver optimized ML models at scale.
Evangelize best practices across the entire engineering and modeling lifecycles.
Mentor other engineers and help recruit and nurture top engineering talent.

What we're looking for

At least 10 years of experience designing and building data-intensive solutions using distributed computing.
At least 6 years of experience programming in C, C++, Python, or Scala.
At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.
Master's Degree (preferred).
3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models (preferred).
2+ years of experience using Dask, RAPIDS, or in High Performance Computing (preferred).
2+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn) (preferred).