Senior ML Engineer — Scale Production AI

Capital One; Plano (TX); On-site; USD 286,000 - 327,000; Full time

Job summary

Capital One is seeking a Senior Staff Machine Learning Engineer to advance AI transformations and scale production models. The role collaborates with Product, Architecture, Engineering and Data Science teams to deliver ML solutions in the financial services space.

The candidate will lead major ML initiatives, optimize data pipelines, and deploy models in cloud environments using Kubernetes. Strong leadership and communications skills are expected.

Qualifications

• Bachelor's or higher in Computer Science, ML or related quantitative field.
• At least 8 years of experience with ML frameworks and distributed systems.
• Experience deploying ML solutions in production on cloud platforms.

Responsibilities

• Deliver ML models and software components solving business problems with Product, Architecture, Engineering, and Data Science teams.
• Drive creation and evolution of ML models and software for intelligent systems.
• Lead large-scale ML initiatives with customer focus.
• Leverage cloud-based architectures to deliver optimized ML models at scale.
• Optimize data pipelines to feed ML models.
• Use Python, Scala, Java, and GoLang.
• Leverage Dask and RAPIDS for compute efficiency.
• Evangelize best practices across engineering and modeling lifecycles.
• Help recruit and retain top engineering talent.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

AWS

GCP

Azure

Distributed systems

Education

Bachelor's Degree or higher in CS/ML or related field

Master's or Doctoral Degree in CS/EE/Math or related field

Tools

Dask

RAPIDS

Job description

Capital One is seeking a Senior Staff Machine Learning Engineer to advance AI transformations and scale production models. The role collaborates with Product, Architecture, Engineering and Data Science teams to deliver ML solutions in the financial services space.

The candidate will lead major ML initiatives, optimize data pipelines, and deploy models in cloud environments using Kubernetes. Strong leadership and communications skills are expected.