Lead Machine Learning Engineer, Finance Tech
Company: Capital One
Location: Cambridge
Posted on: April 25, 2024
Job Description:
Center 2 (19050), United States of America, McLean, VirginiaLead
Machine Learning Engineer, Finance TechAs a Capital One Machine
Learning Engineer (MLE), you'll be part of an Agile team dedicated
to productionizing machine learning (ML) 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. -The EDML (Enterprise.
Data. Machine Learning.) organization delivers exceptional
technology, products, services and processes to support our Data
and Machine Learning ecosystems and core functions that support
holistic operations for Capital One as an enterprise.As a member of
EDML's Finance Tech Machine Learning team, you will support Capital
One's finance and emerging business teams across the company. You
will partner with internal customers to define and develop new
features and capabilities utilizing Machine Learning and AI-enabled
techniques to build solutions for financial transactions,
reconciliations, data anomaly detection, automated regulatory
solutions, forecasting cash flows, and more.We are seeking a
passionate technologist who will not only help us build these
systems from the ground up, but who can think creatively about the
future, and help our team grow rapidly by interacting with
stakeholders and creating business cases. We are seeking a leader
who can influence at the executive level - and coach junior
engineers on the team. The Lead Engineer will be an individual
technical contributor who has a solid AI/ML foundation, and will
help our team accelerate our deliverables.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 systemsPreferred 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 with Generative AI models or tools
- 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 for this position.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, Boston , Lead Machine Learning Engineer, Finance Tech, Accounting, Auditing , Cambridge, Massachusetts
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