Lead Machine Learning Engineer (Python, Analytics)
Company: Capital One
Location: Fredericksburg
Posted on: April 17, 2024
|
|
Job Description:
Center 1 (19052), United States of America, McLean, VirginiaLead
Machine Learning Engineer (Python, Analytics)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 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
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 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.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, Dale City , Lead Machine Learning Engineer (Python, Analytics), Engineering , Fredericksburg, Virginia
Click
here to apply!
|