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About the Role

At Capital One, we are creating responsible and reliable AI systems to change banking for good. We are seeking to leverage AI and ML to create real-time, personalized customer experiences and are committed to building world-class applied science and engineering teams to deliver breakthrough product experiences and scalable, high-performance AI infrastructure. You will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses.

Responsibilities

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
At least 4 years of experience programming with Python, Go, Scala, or Java
6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
Experience designing, developing, delivering, and supporting AI services
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

Skills

MLX
Agentic AI
Gen AI platform Services
AI
ML
Python
Go
Scala
Java
C++
C#
Golang
AWS Ultraclusters
Huggingface
VectorDBs
Nemo Guardrails
PyTorch
LLM Inference
Similarity Search
VectorDBs
Guardrails
Memory

Location

McLean, VA
Cambridge, MA
New York, NY
San Francisco, CA
San Jose, CA

Work Type

Full-time

Experience Level

Lead

Education Level

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

Salary/Compensations

McLean, VA: $197,300 - $225,100
Cambridge, MA: $197,300 - $225,100
New York, NY: $215,200 - $245,600
San Francisco, CA: $215,200 - $245,600
San Jose, CA: $215,200 - $245,600

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

About the Company

At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.