Lead Machine Learning Engineer (Enterprise Platforms Technology)
Company: Capital One
Location: New York City
Posted on: January 20, 2026
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Job Description:
Lead Machine Learning Engineer (Enterprise Platforms Technology)
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. Enterprise Platforms Technology
(EPTech) comprises many of Capital One’s most important enterprise
platforms. We play an essential role in establishing practices for
building technology solutions across the company, while also
delivering capabilities that exemplify those practices. 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 Java
At least 2 years of experience building, scaling, and optimizing ML
systems Preferred Qualifications: Master's or doctoral degree in
computer science, electrical engineering, mathematics, or a similar
field 3 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 code 2 years of experience
with data gathering and preparation for ML models 2 years of people
leader experience 1 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 Platform Experience 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, E-2, E-3, L-1 and O-1, or any EADs or other forms of
work authorization that require immigration support from an
employer). 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, NY: $215,200 - $245,600
for Lead Machine Learning Engineer 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 (EOE,
including disability/vet) committed to non-discrimination in
compliance with applicable federal, state, and local laws. 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, Parsippany-Troy Hills Township , Lead Machine Learning Engineer (Enterprise Platforms Technology), IT / Software / Systems , New York City, New Jersey