Senior ML Engineer — Scalable AI & Production Systems

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

Job summary

Capital One is seeking a Senior Staff Machine Learning Engineer to lead large-scale ML initiatives, deploy production ML systems in cloud environments, and optimize data pipelines. You will collaborate with Product, Architecture, Engineering, and Data Science teams to deliver models that solve complex financial services problems.

The role requires extensive experience with Python/Java/Golang/C++, ML frameworks, distributed systems, and Kubernetes, along with a track record of leadership and

Qualifications

• Bachelor's degree or higher in Computer Science, ML or related quantitative field.
• 10+ years of programming in Python, Java, Golang or C++.
• 8+ years of ML experience with PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn).
• 8+ years in large-scale distributed systems (Spark, Ray) for AI data.
• 8+ years deploying ML in production using cloud (AWS, GCP, Azure) and Kubernetes.

Responsibilities

• Deliver ML models and software components solving complex business problems.
• Lead large-scale ML initiatives with customer focus.
• Drive creation and evolution of ML models and software for intelligent systems.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Optimize data pipelines to feed ML models.
• Use Python, Java, Golang, and GoLang for production ML software.
• Promote best practices across engineering and modeling lifecycles.
• Help recruit and mentor top engineering talent.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Dask

RAPIDS

Pandas

NumPy

Scikit-learn

Education

Bachelor's degree or higher in Computer Science or related quantitative field

Tools

Docker

Job description

Capital One is seeking a Senior Staff Machine Learning Engineer to lead large-scale ML initiatives, deploy production ML systems in cloud environments, and optimize data pipelines. You will collaborate with Product, Architecture, Engineering, and Data Science teams to deliver models that solve complex financial services problems.

The role requires extensive experience with Python/Java/Golang/C++, ML frameworks, distributed systems, and Kubernetes, along with a track record of leadership and