Sr. Distinguished Applied Researcher - Capital One
Company: Capital One
Location: Fort Worth
Posted on: April 17, 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, Keller , Sr. Distinguished Applied Researcher - Capital One, Other , Fort Worth, Texas
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