Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: New York, NY
Salary: $250,800–$286,200 / yr
Posted: 8 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 $219k

This role $268k

$173k most similar roles pay here $298k

This role pays more than 90% of similar roles. Most pay $192,050–$246,150 — the shaded band above. At the midpoint, this role pays about $268k versus about $219k 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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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 technical design, developing model and application code, and ensuring high availability for machine learning platforms. The engineer will build and deliver models that solve real-world business problems, construct optimized data pipelines, and manage the lifecycle of models in production through retraining and monitoring. Key responsibilities include implementing continuous integration and deployment best practices while ensuring responsible and explainable AI. Candidates should possess expertise in Python, Scala, or Java, along with experience in distributed computing and cloud-based architectures. The role utilizes frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow to solve complex problems involving model training, hyperparameter tuning, and feature selection within a large-scale enterprise environment.

Skills

Machine Learning Python Scala Java PyTorch TensorFlow scikit-learn Spark Dask AWS Azure Google Cloud Platform 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 using Python, Scala, or Java.
Construct optimized data pipelines to feed machine learning models.
Build and manage cloud-based architectures to deliver optimized ML models at scale.
Retrain, maintain, and monitor machine learning models in production environments.
Implement CI/CD best practices, including test automation and monitoring, for model deployment.
Ensure all code follows best practices for Responsible and Explainable AI and risk management.

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 deploying ML solutions in public clouds like AWS, Azure, or Google Cloud Platform.
4+ years of experience with industry frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
3+ years of experience building production-ready data pipelines and developing performant, resilient code.

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