LEAD MACHINE LEARNING ENGINEER - CAPITAL ONE
Company: Capital One
Location: Melrose
Posted on: November 1, 2024
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Job Description:
Center 3 (19075), United States of America, McLean, VirginiaLead
Machine Learning EngineerAs a Capital One Machine Learning Engineer
(MLE), you'll be part of an Agile team dedicated to productionizing
machine learning applications and systems at scale. You'll
participate in the detailed technical design, development, and
implementation of machine learning applications using existing and
emerging technology platforms. You'll focus on machine learning
architectural design, develop and review model and application
code, and ensure high availability and performance of our machine
learning applications. You'll have the opportunity to continuously
learn and apply the latest innovations and best practices in
machine learning engineering. Team DescriptionOur team is on the
cutting edge of GenAI and at the center of bringing our vision for
AI at Capital One to life. The work of the AI Training Team touches
every aspect of the model development life cycle and our deployed
models in production drive business impact with visibility from our
C-Suite.Our team creates unprecedented amounts of high quality data
for training and testing GenAI models; we care about how it's
created, what's in those datasets, and the impact they haveWe are
invested in building capabilities for evaluating and monitoring
generative models; these methods must be state of the art, easy to
use, and trusted by our users and contributorsHorizontal
capabilities enable vertical use case work; the team builds search,
summarization, RAG, and agentic workflows for integration in
production applications across the companyWe learn from our
colleagues, attend conferences, publish papers, and maintain strong
connections to the research community. Everyone on this team has a
role in realizing GenAI capabilities at Capital One, and we're
excited to find experienced talent to join us.What you'll do in the
role: The MLE role overlaps with many disciplines, such as Ops,
Modeling, and Data Engineering. In this role, you'll be expected to
perform many ML engineering activities, including one or more of
the following:Design, build, and/or deliver ML models and
components that solve real-world business problems, while working
in collaboration with the Product and Data Science teams. Inform
your ML infrastructure decisions using your understanding of ML
modeling techniques and issues, including choice of model, data,
and feature selection, model training, hyperparameter tuning,
dimensionality, bias/variance, and validation).Solve complex
problems by writing and testing application code, developing and
validating ML models, and automating tests and deployment.
Collaborate as part of a cross-functional Agile team to create and
enhance software that enables state-of-the-art big data and ML
applications. Retrain, maintain, and monitor models in
production.Leverage or build cloud-based architectures,
technologies, and/or platforms to deliver optimized ML models at
scale.Construct optimized data pipelines to feed ML models.
Leverage continuous integration and continuous deployment best
practices, including test automation and monitoring, to ensure
successful deployment of ML models and application code. Ensure all
code is well-managed to reduce vulnerabilities, models are
well-governed from a risk perspective, and the ML follows best
practices in Responsible and Explainable AI. Use programming
languages like Python, Scala, or Java. Basic
Qualifications:Bachelor's degree At least 6 years of experience
designing and building data-intensive solutions using distributed
computing (Internship experience does not apply)At least 4 years of
experience programming with Python, Scala, or JavaAt least 2 years
of experience building, scaling, and optimizing ML systemsPreferred
Qualifications:Master's or doctoral degree in computer science,
electrical engineering, mathematics, or a similar field3+ years of
experience building production-ready data pipelines that feed ML
models 3+ years of on-the-job experience with an industry
recognized ML framework such as scikit-learn, PyTorch, Dask, Spark,
or TensorFlow 2+ years of experience developing performant,
resilient, and maintainable code2+ years of experience with data
gathering and preparation for ML models2+ years of people leader
experience1+ years of experience leading teams developing ML
solutions using industry best practices, patterns, and automation
Experience developing and deploying ML solutions in a public cloud
such as AWS, Azure, or Google Cloud PlatformExperience designing,
implementing, and scaling complex data pipelines for ML models and
evaluating their performance ML industry impact through conference
presentations, papers, blog posts, open source contributions, or
patents At this time, Capital One will not sponsor a new applicant
for employment authorization, or offer any immigration related
support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1
CPT, J-1, TN, or another type of work authorization).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): $201,400 - $229,900 for Lead
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 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.comCapital 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, Portland , LEAD MACHINE LEARNING ENGINEER - CAPITAL ONE, Engineering , Melrose, Maine
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