Lead Machine Learning Engineer (Enterprise Platforms Technology)

Capital One Financial

Quick summary

Work type: On-site
Location: New York, NY · McLean, VA
Salary: $197,300–$225,100 / yr
Posted: 58 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $221k

This role $211k

$172k most similar roles pay here $268k

This role pays less than 53% of similar roles. Most pay $195,100–$246,150 — the shaded band above. At the midpoint, this role pays about $211k versus about $221k for comparable roles.

Based on 239 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 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead Machine Learning Engineer (Enterprise Platforms Technology)

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The Lead Machine Learning Engineer role is part of the Enterprise Platforms Technology team and targets a senior-level professional with extensive experience in machine learning. This individual will lead the development and deployment of advanced ML models to enhance enterprise solutions, focusing on scalability and performance optimization. Day-to-day responsibilities include collaborating with cross-functional teams to identify business needs, designing innovative algorithms, and implementing robust data pipelines using Python, TensorFlow, and Spark. The ideal candidate possesses expertise in cloud platforms like AWS or Azure, as well as a deep understanding of machine learning frameworks and best practices for large-scale systems. This role addresses critical enterprise challenges by leveraging cutting-edge technologies to drive impactful solutions at scale.

Skills

Python TensorFlow PyTorch Scikit-learn Pandas NumPy MLOps Kubernetes Docker AWS CI/CD Git Jupyter Notebook PostgreSQL MongoDB

What you'll do

Design and implement advanced machine learning models to solve complex business problems.
Optimize existing ML systems for efficiency and scalability across enterprise platforms.
Conduct research on cutting-edge AI techniques and integrate them into production environments.
Mentor junior engineers and provide technical guidance on ML projects.
Monitor model performance and iterate improvements based on real-time data analytics.

What we're looking for

Bachelor’s Degree or higher in Computer Science, Engineering, or related field.
Extensive experience in machine learning and deep learning techniques.
Proficiency in Python and other programming languages relevant to data science.
Strong background in building scalable and efficient ML platforms.
Experience with cloud-based solutions for deploying machine learning models.

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