Senior Lead Engineer - Generative AI Infrastructure (Remote-Eligible)
Company: Capital One
Location: Washington
Posted on: April 25, 2024
Job Description:
NYC 299 Park Avenue (22957), United States of America, New York,
New YorkSenior Lead Engineer - Generative AI Infrastructure
(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 -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.Basic Qualifications:
- 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 8 years of experience programming with Python, Go,
Scala, or Java
- At least 1 year of experience with HPCs, vector embedding, or
semantic search technologies
- At least 1 year of experience building, scaling, and optimizing
training or inferencing systems for deep neural networks -Preferred
Qualifications:
- 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):
$234,700 - $267,900 for Sr. Lead Machine Learning EngineerSan
Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr.
Lead Machine Learning EngineerRemote (Regardless of Location):
$198,900 - $227,000 for Sr. Lead Machine Learning
EngineerCandidates 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.This role is expected to accept applications for a
minimum of 5 business days.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.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.comCapital One does not
provide, endorse nor guarantee and is not liable for third-party
products, services, educational tools or other information
available through this site.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).
Keywords: Capital One, Alexandria , Senior Lead Engineer - Generative AI Infrastructure (Remote-Eligible), Engineering , Washington, Virginia
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