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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 at the forefront of enterprises leveraging AI, bringing humanity and simplicity to banking through AI & ML applications. 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 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 6 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 4 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, or Java
• 7 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, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
• 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
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Skills

• AI
• ML
• Python
• Go
• Scala
• Java
• AWS Ultraclusters
• Huggingface
• VectorDBs
• Nemo Guardrails
• PyTorch
• LLM Optimization
• LLM Inference
• Similarity Search
• VectorDBs
• Guardrails
• Memory
• C++
• C#

Location

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

Work Type

• Full-time

Experience Level

• Sr. 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

• Cambridge, MA: $229,900 - $262,400
• McLean, VA: $229,900 - $262,400
• New York, NY: $250,800 - $286,200
• San Francisco, CA: $250,800 - $286,200
• San Jose, CA: $250,800 - $286,200

Benefits

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

About the Company

• 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.

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 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.