Senior Distinguished Engineer

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: McLean, VA
Employment: Full-time
Posted: 127 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 $203k

$139k $273k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $152,000–$254,931.

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 · Senior Distinguished Engineer

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The Sr. Distinguished Engineer joins the Machine Learning Engineering team to provide technical leadership for productionizing machine learning applications and systems at scale. This role involves participating in detailed technical designs, developing model and application code, and ensuring high availability and performance. The engineer will build software components to solve challenging business problems in the financial services industry, optimize data pipelines, and lead large-scale initiatives using cloud-based architectures. Key technical requirements include proficiency in Python, Scala, and C/C++, along with experience using Dask, RAPIDS, and the PyData ecosystem, including NumPy, Pandas, and Scikit-learn. The position requires expertise in the full machine learning development lifecycle, distributed computing, and high-performance computing to deliver state-of-the-art intelligent systems in a business-critical setting.

What does a Engineer earn?

Median $178175 from 251 postings across 54 companies.

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Skills

Machine Learning Python Scala C++ 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 business problems in financial services.
Lead the technical design, development, and implementation of large-scale machine learning applications.
Optimize data pipelines to efficiently feed machine learning models.
Leverage cloud-based architectures and technologies like Dask and RAPIDS to deliver models at scale.
Develop and review model and application code using Python, Scala, or C/C++.
Evangelize best practices across all aspects of the engineering and modeling lifecycles.
Recruit, nurture, and retain top engineering talent to build high-performing teams.

What we're looking for

At least 10 years of experience designing and building data-intensive solutions using distributed computing.
At least 7 years of experience programming in C, C++, Python, or Scala.
At least 4 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).
3+ years of experience using Dask, RAPIDS, or in High Performance Computing (preferred).
3+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn) (preferred).

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