Sr. Director, Applied Research - Capital One
Company: Capital One
Location: Mount Sinai
Posted on: April 24, 2024
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Job Description:
Center 1 (19052), United States of America, McLean, VirginiaSr.
Director, Applied ResearchOverview: At Capital One, we are creating
trustworthy and reliable 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. 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. Team Description: The AI
Foundations team is at the center of bringing our vision for AI at
Capital One to life. Our work touches every aspect of the research
life cycle, from partnering with Academia to building production
systems. We work with product, technology and business leaders to
apply the state of the art in AI to our business. This is a people
manager role that will lead teams to drive strategic direction
through collaboration with Applied Science, Engineering and Product
leaders across Capital One. As a well-respected people leader, you
will guide and mentor a team of applied scientists. You will be
expected to be an external leader representing Capital One in the
research community, collaborating with prominent faculty members in
the relevant AI research community. In this role, you will: Partner
with a cross-functional team of data scientists, software
engineers, machine learning engineers and product managers to
deliver AI-powered products that change how customers interact with
their money. Leverage a broad stack of technologies - Pytorch, AWS
Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to
reveal the insights hidden within huge volumes of numeric and
textual data. Build AI foundation models through all phases of
development, from design through training, evaluation, validation,
and implementation. Engage in high impact applied research to take
the latest AI developments and push them into the next generation
of customer experiences. Flex your interpersonal skills to
translate the complexity of your work into tangible business goals.
The Ideal Candidate: You love the process of analyzing and
creating, but also share our passion to do the right thing. You
know at the end of the day it's about making the right decision for
our customers. Innovative. You continually research and evaluate
emerging technologies. You stay current on published
state-of-the-art methods, technologies, and applications and seek
out opportunities to apply them. Creative. You thrive on bringing
definition to big, undefined problems. You love asking questions
and pushing hard to find answers. You're not afraid to share a new
idea. A leader. You challenge conventional thinking and work with
stakeholders to identify and improve the status quo. You're
passionate about talent development for your own team and beyond.
Technical. You're comfortable with open-source languages and are
passionate about developing further. You have hands-on experience
developing AI foundation models and solutions using open-source
tools and cloud computing platforms. Has a deep understanding of
the foundations of AI methodologies. Experience building large deep
learning models, whether on language, images, events, or graphs, as
well as expertise in one or more of the following: training
optimization, self-supervised learning, robustness, explainability,
RLHF. An engineering mindset as shown by a track record of
delivering models at scale both in terms of training data and
inference volumes. Experience in delivering libraries, platform
level code or solution level code to existing products. A
professional with a track record of coming up with new ideas or
improving upon existing ideas in machine learning, demonstrated by
accomplishments such as first author publications or projects.
Possess the ability to own and pursue a research agenda, including
choosing impactful research problems and autonomously carrying out
long-running projects. Key Responsibilities: Partner with a
cross-functional team of scientists, machine learning engineers,
software engineers, and product managers to deliver AI-powered
platforms and solutions that change how customers interact with
their money. Build AI foundation models through all phases of
development, from design through training, evaluation, validation,
and implementation. Engage in high impact applied research to take
the latest AI developments and push them into the next generation
of customer experiences. Leverage a broad stack of technologies -
Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and
more - to reveal the insights hidden within huge volumes of numeric
and textual data. Flex your interpersonal skills to translate the
complexity of your work into tangible business goals. Basic
Qualifications: Ph.D. plus at least 6 years of experience in
Applied Research or M.S. plus at least 8 years of experience in
Applied Research At least 5 years of people leadership experience
Preferred Qualifications: PhD in Computer Science, Machine
Learning, Computer Engineering, Applied Mathematics, Electrical
Engineering or related fields LLM PhD focus on NLP or Masters with
10 years of industrial NLP research experience Core contributor to
team that has trained a large language model from scratch (10B +
parameters, 500B+ tokens) Numerous publications at ACL, NAACL and
EMNLP, Neurips, ICML or ICLR on topics related to the pre-training
of large language models (e.g. technical reports of pre-trained
LLMs, SSL techniques, model pre-training optimization) Has worked
on an LLM (open source or commercial) that is currently available
for use Demonstrated ability to guide the technical direction of a
large-scale model training team Experience working with 500+ node
clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+
tokens Experience with common training optimization frameworks
(deep speed, nemo) Behavioral Models PhD focus on topics in
geometric deep learning (Graph Neural Networks, Sequential Models,
Multivariate Time Series) Member of technical leadership for model
deployment for a very large user behavior model Multiple papers on
topics relevant to training models on graph and sequential data
structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph
models to greater than 50m nodes Experience with large scale deep
learning based recommender systems Experience with production
real-time and streaming environments Contributions to common open
source frameworks (pytorch-geometric, DGL) Proposed new methods for
inference or representation learning on graphs or sequences Worked
datasets with 100m+ users Optimization (Training & Inference) PhD
focused on topics related to optimizing training of very large
language models 5+ years of experience and/or publications on one
of the following topics: Model Sparsification, Quantization,
Training Parallelism/Partitioning Design, Gradient Checkpointing,
Model Compression Finetuning PhD focused on topics related to
guiding LLMs with further tasks (Supervised Finetuning,
Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
Demonstrated knowledge of principles of transfer learning, model
adaptation and model guidance Experience deploying a fine-tuned
large language model Data Preparation Numerous Publications
studying tokenization, data quality, dataset curation, or labeling
Leading contributions to one or more large open source corpus (1
Trillion + tokens) Core contributor to open source libraries for
data quality, dataset curation, or labeling 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): $368,000 - $420,000 for Sr Director, Applied Research San
Francisco, California (Hybrid On-site): $389,900 - $444,900 for Sr
Director, Applied Research 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. 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): $368,000 - $420,000 for Sr
Director, Applied ResearchSan Francisco, California (Hybrid
On-Site): $389,900 - $444,900 for Sr Director, Applied
ResearchCandidates 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.com 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, Brentwood , Sr. Director, Applied Research - Capital One, Executive , Mount Sinai, New York
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