Sr. Distinguished Applied Researcher
Company: Capital One
Location: Astoria
Posted on: October 31, 2024
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Job Description:
Center 1 (19052), United States of America, McLean, VirginiaSr.
Distinguished Applied ResearcherOverview:
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 an individual contributor (IC) role driving strategic
direction through collaboration with Applied Science, Engineering
and Product leaders across Capital One. As a well-respected IC
leader, you will guide and mentor a team of applied scientists and
their managers without being a direct people leader. 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
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. Distinguished Applied Researcher
San Francisco, California (Hybrid On-site):
$389,900 - $444,900 for Sr. Distinguished Applied Researcher
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.
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, New York , Sr. Distinguished Applied Researcher, Other , Astoria, New York
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