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 Sr. Lead Engineer, Generative AI Infrastructure to help us build the foundations of our AI capabilities. You will work on a wide range of initiatives, whether that’s building large-scale distributed training clusters, or deploying LLMs on GPU instances for real-time applications and decisioning systems, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work closely with our cloud and container infrastructure teams as well as our world-class team of AI researchers to design and implement key capabilities. Examples of projects you will work on:
Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud.
Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries.
Design and build run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud.
Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our capabilities.
Capital One is open to hiring a Remote Employee for this opportunity.
Bachelor's degree in Computer Science, Computer Engineering or a technical field
At least 8 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience with HPCs, vector embedding, or semantic search technologies
At least 4 years of experience programming with Python, Go, Scala, or Java
At least 3 years of experience building, scaling, and optimizing training and inferencing systems for deep neural networks
Master's or Doctoral degree in Computer science, Computer Engineering, Electrical engineering, Mathematics, or a similar field.
Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures.
Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML etc.
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.
Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking.
Capital One will consider sponsoring a new qualified 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): $230,100 - $262,700 for Sr. Lead Machine Learning EngineerSan Francisco, California (Hybrid On-Site): $243,800 - $278,200 for Sr. Lead Machine Learning EngineerRemote (Regardless of Location): $195,000 - $222,600 for Sr. 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.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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.
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For technical support or questions about Capital One's recruiting process, please send an email to Careers@https://capitalone.com
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Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).