Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: New York, NYSan Francisco, CAMcLean, VACambridge, MASan Jose, CA
Salary: $229,900–$262,400 / yr
Posted: 91 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $225k

This role $246k

$175k most similar roles pay here $275k

This role pays more than 68% of similar roles. Most pay $195,112–$254,750 — the shaded band above. At the midpoint, this role pays about $246k versus about $225k for comparable roles.

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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Lead Machine Learning Engineer

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As a Sr. Lead Machine Learning Engineer, you will join an Agile team dedicated to productionizing machine learning applications and systems at scale. You will perform critical engineering activities including designing, building, and delivering ML models that solve real-world business problems while collaborating with Product and Data Science teams. Your daily responsibilities involve developing and reviewing model code, constructing optimized data pipelines, and ensuring high availability through automated testing and deployment. You will manage the full lifecycle of machine learning by retraining, monitoring, and governing models for risk and explainability. The role requires proficiency in Python, Scala, or Java, along with experience using frameworks like scikit-learn, PyTorch, Dask, Spark, Kubeflow, or TensorFlow. You will leverage cloud-based architectures to deliver high-performance solutions within a complex technical environment focused on big data and advanced machine learning applications.

Skills

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

What you'll do

Design, build, and deliver machine learning models and components that solve real-world business problems.
Develop and review model and application code while ensuring high availability and performance of ML systems.
Construct optimized data pipelines to feed machine learning models.
Retrain, maintain, and monitor machine learning models in production environments.
Build and manage cloud-based architectures and technologies to deliver optimized models at scale.
Implement CI/CD best practices, including test automation and monitoring, for model and code deployment.
Ensure all models follow best practices regarding Responsible and Explainable AI and risk governance.

What we're looking for

Bachelor's degree required; Master's or doctoral degree in a related field preferred.
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.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
At least 4 years of experience with an industry recognized ML framework like scikit-learn, PyTorch, Dask, Spark, Kubeflow, or TensorFlow.
At least 3 years of experience building production-ready data pipelines and developing performant, resilient code.

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