Senior Lead Machine Learning Engineer, Enterprise Platforms Technology

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: New York, NY
Employment: Full-time
Posted: 54 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $206k

$142k $252k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $169,550–$241,750.

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.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Lead Machine Learning Engineer, Enterprise Platforms Technology

Role Posting Log in to save

The Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology) joins an Agile team within Enterprise Platforms Technology to productionize machine learning applications and systems at scale. This role involves the technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Key responsibilities include building ML models and components to solve business problems, constructing optimized data pipelines, and maintaining models in production. The engineer will ensure high availability, performance, and governance while following best practices in Responsible and Explainable AI. Required technical skills include programming in Python, Scala, or Java, along with experience in distributed computing and ML frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow. The role focuses on delivering optimized ML models within cloud-based architectures to solve complex data problems.

Skills

Python Scala Java PyTorch TensorFlow Spark scikit-learn Dask AWS Azure Google Cloud Platform Distributed Computing Data Pipelines Agile Explainable AI

What you'll do

Design, build, and deliver machine learning models and components to solve real-world business problems.
Write and test application code to solve complex problems and automate deployment processes.
Construct and optimize data pipelines to feed machine learning models.
Retrain, maintain, and monitor machine learning models in production environments.
Build and leverage cloud-based architectures to deliver optimized ML models at scale.
Implement continuous integration and continuous deployment best practices, including test automation and monitoring.
Ensure all code and models follow best practices for Responsible and Explainable AI.

What we're looking for

At least 8 years of experience designing and building data-intensive solutions using distributed computing.
At least 4 years of experience programming with Python, Scala, or Java.
At least 3 years of experience building, scaling, and optimizing ML systems.
At least 2 years of experience leading teams developing ML solutions.
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred).
4+ years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred).

Save