Senior Manager, Machine Learning Engineering
Company: Capital One
Location: Cambridge
Posted on: October 24, 2024
Job Description:
Center 3 (19075), United States of America, McLean,
VirginiaSenior Manager, Machine Learning EngineeringAs 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 8 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 3 years of experience building, scaling, and
optimizing ML systems
- At least 2 years of experience leading teams developing ML
solutions
- At least 4 years of people management experience. - -Preferred
Qualifications:
- Master's or doctoral degree in computer science, electrical
engineering, mathematics, or a similar field -
- 4+ years of on-the-job experience with an industry recognized
ML framework such as scikit-learn, PyTorch, Dask, Spark, or
TensorFlow -
- 3+ years of experience developing performant, resilient, and
maintainable code
- 3+ years of experience with data gathering and preparation for
ML models
- Experience developing and deploying ML solutions in a public
cloud such as AWS, Azure, or Google Cloud Platform -
- 3+ years of experience building production-ready data pipelines
that feed ML models
- Ability to communicate complex technical concepts clearly to a
variety of audiences
- ML industry impact through conference presentations, papers,
blog posts, open source contributions, or patents - -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): $234,700 - $267,900 for Sr. Mgr, Machine Learning
EngineeringSan Francisco and San Jose, California (Hybrid On-Site):
$248,700 - $283,800 for Sr. Mgr, Machine Learning
EngineeringCandidates 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, Cambridge , Senior Manager, Machine Learning Engineering, Executive , Cambridge, Massachusetts
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