Lead Machine Learning Engineer

Capital One Financial

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: San Jose, CASan Francisco, CAMcLean, VACambridge, MANew York, NY
Salary: $197,300–$225,100 / yr
Posted: 65 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k

This role $211k

$175k most similar roles pay here $273k

This role pays less than 59% of similar roles. Most pay $194,850–$254,750 — the shaded band above. At the midpoint, this role pays about $211k 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.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead Machine Learning Engineer

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Lead Machine Learning Engineer As part of an Agile team, the Lead Machine Learning Engineer will focus on productionizing machine learning applications and systems at scale. This role involves technical design, developing and reviewing model code, and ensuring high availability for machine learning applications. Key responsibilities include building components to solve real-world business problems, managing infrastructure decisions like feature selection and hyperparameter tuning, and constructing optimized data pipelines. The candidate will work with cross-functional teams to develop software for big data applications while maintaining models in production. Technical requirements include proficiency in Python, Go, Scala, or Java, along with experience using frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. Additionally, the role requires expertise in cloud-based architectures like AWS and Kubernetes to deliver optimized models within a framework of responsible and explainable AI.

Skills

Machine Learning Python Go Scala Java AWS Kubernetes PyTorch TensorFlow scikit-learn Spark Dask Data Pipelines Agile Distributed Computing

What you'll do

Design, build, and deliver machine learning models and components to solve real-world business problems.
Develop and review high-quality application code for production-scale machine learning systems.
Inform infrastructure decisions based on model training, hyperparameter tuning, and feature selection.
Construct and optimize data pipelines to feed machine learning models.
Retrain, maintain, and monitor machine learning models in production environments.
Build and manage cloud-based architectures using technologies like AWS and Kubernetes.
Implement CI/CD best practices, including test automation and monitoring for model deployment.
Ensure all models follow best practices for Responsible and Explainable AI.

What we're looking for

Bachelor's degree required; Master's or Doctoral degrees in related fields are preferred.
At least 6 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 2 years of experience building, scaling, and optimizing machine learning systems.
At least 3 years of experience with industry-recognized ML frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
At least 2 years of experience developing performant, resilient, and maintainable code using Python or Go.
Experience building production-ready data pipelines and managing infrastructure using Kubernetes and public cloud platforms like AWS.
Work authorization that require immigration support from an employer.

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