Senior Engineer - Generative AI Product Engineering (Remote-Eligible)
Company: Capital One
Location: New York
Posted on: October 17, 2024
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Job Description:
Center 3 (19075), United States of America, McLean,
VirginiaSenior Engineer - Generative AI Product Engineering
(Remote-Eligible)As 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.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 4 years of experience
programming with Python, Scala, or Java (Internship experience does
not apply)At least 3 years of experience designing and building
data-intensive solutions using distributed computingAt least 2
years of on-the-job experience with an industry recognized ML
frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)At
least 1 year of experience productionizing, monitoring, and
maintaining modelsPreferred Qualifications:1+ years of experience
building, scaling, and optimizing ML systems1+ years of experience
with data gathering and preparation for ML models2+ years of
experience developing performant, resilient, and maintainable
codeExperience developing and deploying ML solutions in a public
cloud such as AWS, Azure, or Google Cloud PlatformMaster's or
doctoral degree in computer science, electrical engineering,
mathematics, or a similar field3+ years of experience with
distributed file systems or multi-node database
paradigmsContributed to open source ML softwareAuthored/co-authored
a paper on a ML technique, model, or proof of concept3+ years of
experience building production-ready data pipelines that feed ML
modelsExperience designing, implementing, and scaling complex data
pipelines for ML models and evaluating their performanceAt 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): $165,100 - $188,500 for Senior Machine
Learning EngineerSan Francisco and San Jose, California (Hybrid
On-Site): $174,900 - $199,700 for Senior 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, Levittown , Senior Engineer - Generative AI Product Engineering (Remote-Eligible), Engineering , New York, New York
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