Senior AI Systems Engineer – Scalable Foundation Models

Capital One; Cambridge (MA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One in Cambridge, MA is seeking engineers to build responsible AI systems that power real-time, personalized experiences for customers. You will work with engineers, researchers, PMs, and product managers to deliver AI-powered products and scale them across platforms.

Responsibilities include designing and deploying AI components, optimizing training and inference, and ensuring governance, security, and observability.

Qualifications

• Bachelor's or Master's degree in CS/AI/EE/CE with relevant AI/ML experience.
• 4+ years developing AI/ML algorithms or technologies.
• Strong Python, Go, Scala, CUDA, or Java programming experience.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products that affect associates and customers.
• Design, develop, test, deploy, and support AI software components (foundation models, inference, agents, vector search).
• Leverage Open Source and SaaS AI tech such as AWS Ultraclusters, Huggingface, PyTorch.
• Optimize foundation model performance for scale, cost, latency, and throughput.
• Define and maintain architecture and service-level objectives for AI systems.
• Collaborate with infrastructure to optimize GPU/TPU utilization and model pipelines.
• Lead technical reviews for deployments ensuring security and governance.
• Mentor junior engineers on scalable design and production translation.

Skills

Python

Go

Scala

CUDA

Java

Distributed systems

Education

Bachelor's degree in CS/AI/EE/CE

Master's degree in CS/AI/EE/CE

Tools

AWS

Google Cloud

Azure

Huggingface

PyTorch

VectorDBs

C++

Job description

Capital One in Cambridge, MA is seeking engineers to build responsible AI systems that power real-time, personalized experiences for customers. You will work with engineers, researchers, PMs, and product managers to deliver AI-powered products and scale them across platforms.

Responsibilities include designing and deploying AI components, optimizing training and inference, and ensuring governance, security, and observability.