Senior AI Foundations & LLM Systems Engineer

Capital One

Cambridge (MA)

Vor Ort

USD 230.000 - 262.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Capital One is seeking an AI Engineer 5 to build responsible AI systems in Cambridge, MA. You will design and deploy AI software components, including foundation models, LLMs, agents, and vector search, leveraging Open Source and SaaS technologies.

The role emphasizes scalable, cost-aware AI infrastructure and governance. You will mentor engineers, partner with product managers, and contribute to technical roadmaps while applying ethical AI practices and ensuring high reliability in production

Qualifikationen

  • Bachelor's degree plus 6+ years in AI/ML or Master’s degree plus 4+ years in AI/ML.
  • Proficient programming in Python, Go, Scala, CUDA, or Java.

Aufgaben

  • Partner with cross-functional team to deliver AI-powered products that change how associates work and how customers interact with Capital One.
  • Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents, and multi-agent workflows.
  • Lead cost-performance governance reviews across AI systems, tracking GPU utilization and model throughput.

Kenntnisse

Python
Go
Scala
CUDA
Java

Ausbildung

Bachelor's degree in Computer Science / AI / Electrical Engineering / Computer Engineering or related fields
Master's degree in Computer Science / AI / Electrical Engineering / Computer Engineering or related fields

Tools

AWS
Huggingface
PyTorch
VectorDBs

Jobbeschreibung

Capital One is seeking an AI Engineer 5 to build responsible AI systems in Cambridge, MA. You will design and deploy AI software components, including foundation models, LLMs, agents, and vector search, leveraging Open Source and SaaS technologies.

The role emphasizes scalable, cost-aware AI infrastructure and governance. You will mentor engineers, partner with product managers, and contribute to technical roadmaps while applying ethical AI practices and ensuring high reliability in production

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