Lead Engineer - Generative AI Product Engineering (Remote- Eligible)

Key Skills

Aartificial intelligence, API, Deep neural networks, Generative AI, Java Programming, Leadership, Natural Language Processing (NLP), Neural Networks, Optimization, Python Programming, Scala Programming

Job Description

Lead Engineer - Generative AI Product Engineering (Remote- Eligible)

Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. 

We are looking for an experienced Lead Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure. You will work with a team of world-class AI engineers and researchers to design and implement key API products and services that enable real-time customer-facing applications. Examples of projects you will work on include: 

• Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. 
• Design APIs for performance, real-time applications, scale, ease of use and governance automation. 
• Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience.
• Enable our users to build new GenAI capabilities. 
• Develop tools and processes to monitor API access patterns and operational health.
• Design and implement AI safety and guardrails in the API layer working closely with researchers. 

Capital One is open to hiring a Remote Employee for this opportunity.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering or a technical field
• At least 6 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques 
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing training and inferencing APIs for deep neural networks 

Preferred Qualifications:

• Familiarity with building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users. 
• Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. 
• Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities.
• Familiarity with deploying large neural network models in demanding production environments. 
• Have experience with API security, observability, cloud access control and privacy best practices. 

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York City (Hybrid On-Site): $197,400 - $225,300 for Lead Machine Learning Engineer

San Francisco, California (Hybrid On-Site): $209,200 - $238,700 for Lead Machine Learning Engineer

Remote (Regardless of Location): $167,400 - $191,000 for Lead Machine Learning Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com