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About the Role
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. Our investments in technology infrastructure and world-class talent position us to be at the forefront of enterprises leveraging AI. We 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, agents and multi-agent workflows, 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, PyTorch, and more.
- Invent and introduce state-of-the-art foundation model 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.
- Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems.
- Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
- Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards.
- Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity.
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, CUDA, or Java.
- Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy.
- 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, delivering, and supporting complex AI systems.
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, 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.
- Experience in building agentic AI systems and agentic workflows.
- Passion for staying abreast of the latest AI research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
- Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.
- Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines.
- Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes.
- Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression.
- Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs).
Skills
- AI
- ML
- Machine Learning
- Large Language Models (LLM)
- Agentic AI
- Gen AI
- Foundation Models
- Inference
- VectorDBs
- PyTorch
- Python
- Go
- Scala
- CUDA
- Java
- C++
- C#
- Golang
- AWS
- Google Cloud
- Azure
- Similarity Search
- Guardrails
- Model Evaluation
- Experimentation
- Governance
- Observability
- Cloud Platforms
Location
- Cambridge, MA
- McLean, VA
- New York, NY
- San Francisco, CA
- San Jose, CA
Work Type
- Full-time
Experience Level
- 5 years
- 6 years
- 7 years
- Principal
- Manager-level
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.
- Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
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.
- 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.
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.