Distinguished Engineer, Generative AI Systems (Remote Eligible)
Company: Capital One
Location: San Jose
Posted on: October 15, 2024
Job Description:
Locations: Sales - CA - San Francisco, United States of America,
San Francisco, CaliforniaDistinguished Engineer, Generative AI
Systems (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 Senior Distinguished Engineer, AI
Systems, to help us build the foundations of our enterprise AI
Capabilities. You will work on a wide range of initiatives, whether
that's designing robust, secure infrastructure, building
large-scale distributed training clusters, deploying LLMs on GPU
instances for real-time use cases, or supporting cutting-edge AI
research and development, all in our public cloud infrastructure.
You will work with a team of AI engineers and researchers to
envision the target state of our capabilities while helping to
design and implement key services. Examples of projects you will
work on include: -
- 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 infrastructure for serving large ML models, in
our public cloud. - -
- 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 implement benchmarks to measure the performance of
software systems within AI capabilities and make recommendations on
technology selection
- Develop applications that leverage LLMs and FMs.
- Design and implement capabilities to support MLOps for
foundation models.Capital One is open to hiring a Remote Employee
for this opportunityBasic Qualifications:
- Bachelor's degree in Computer Science, Computer Engineering or
a technical field
- At least 7 years of experience designing and building
distributed computing HPC and large-scale ML systems -
- At least 5 years of experience developing AI and ML algorithms
in Python or C/C++
- At least 3 years of experience with the full ML development
lifecycle using AI and ML frameworks and public cloud. -Preferred
Qualifications:
- Master's degree or PhD in Engineering, Computer Science, a
related technical field, or equivalent practical experience with a
focus on modern AI techniques. -
- Experience designing large-scale distributed platforms and/or
systems in cloud environments such as AWS, Azure, or GCP.
- Experience architecting cloud systems for security,
availability, performance, scalability, and cost.
- Experience with delivering very large models through the MLOps
life cycle from exploration to serving.
- Experience with building GPU clusters in the public cloud with
tightly-coupled storage and networking. -
- Experience with the complete stack for distributed training of
large models including ML compilers, distributed training
frameworks, and ML development frameworks such as Pytorch,
Tensorflow, Lightning etc. -
- Experience with one or multiple areas of AI technology stack
including prompt engineering, guardrails, vector
databases/knowledge bases, LLM hosting and fine-tuning.
- Authored research publications in top peer-reviewed
conferences, or industry-recognized contributions in the space of
neural networks, distributed training and SysML. -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): $274,800 - $313,600 for Distinguished Machine Learning
EngineerSan Francisco, California (Hybrid On-Site): $291,100 -
$332,300 for Distinguished Machine Learning EngineerRemote
(Regardless of Location): $232,900 - $265,800 for Distinguished
Machine Learning EngineerCandidates 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, Madera , Distinguished Engineer, Generative AI Systems (Remote Eligible), Other , San Jose, California
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