Senior Lead Engineer - Generative AI Infrastructure (Remote-Eligible)
Company: Capital One
Location: Boston
Posted on: November 20, 2023
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 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 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): $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 ; 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- or via email at . 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 Capital 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, Boston , Senior Lead Engineer - Generative AI Infrastructure (Remote-Eligible), Engineering , Boston, Massachusetts
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