Applied Researcher I
Company: Capital One
Location: New York
Posted on: November 12, 2024
Job Description:
Center 3 (19075), United States of America, McLean,
VirginiaApplied Researcher IOverview: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. -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 high
quality 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.Basic Qualifications:
- Currently has, or is in the process of obtaining, a PhD, with
an expectation that required degree will be obtained on or before
the scheduled start date or M.S. with at least 2 years of
experience in Applied ResearchPreferred Qualifications:
- PhD in Computer Science, Machine Learning, Computer
Engineering, Applied Mathematics, Electrical Engineering or related
fields
- LLM
- PhD focus on NLP or Masters with 5 years of industrial NLP
research experience
- Multiple publications 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)
- Member of team that has trained a large language model from
scratch (10B + parameters, 500B+ tokens) -
- Publications in deep learning theory -
- Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
- Behavioral Models
- PhD focus on topics in geometric deep learning (Graph Neural
Networks, Sequential Models, Multivariate Time Series)
- 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 deep learning models -
- Multiple years of experience and/or publications on one of the
following topics: Model Sparsification, Quantization, Training
Parallelism/Partitioning Design, Gradient Checkpointing, Model
Compression -
- Experience optimizing training for a 10B+ model -
- Deep knowledge of deep learning algorithmic and/or optimizer
design -
- Experience with compiler design
- 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
- Publications studying tokenization, data quality, dataset
curation, or labeling -
- Contribution to a major open source corpus -
- Contribution to open source libraries for data quality, dataset
curation, or labelingCapital One will consider sponsoring a new
qualified applicant for employment authorization for this
positionThe 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): -$230,000 -
$262,500 for Applied Researcher ISan Francisco, California (Hybrid
On-site): -$243,700 - $278,100 for Applied Researcher ICandidates
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 -. 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 . 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, Philadelphia , Applied Researcher I, Other , New York, Pennsylvania
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