Machine Learning Engineer
Company: Capital One
Location: Richmond
Posted on: May 16, 2022
Job Description:
Center 1 (19052), United States of America, McLean,
VirginiaMachine Learning EngineerAs 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 2 years of experience designing and building
data-intensive solutions using distributed computing (Internship
experience does not apply)
- At least 2 years of experience programming with Python, Scala,
or Java
- At least 1 year of Machine Learning experience with an industry
recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or
TensorFlow)
Preferred Qualifications:
- Experience developing and deploying ML solutions in a public
cloud such as AWS, Azure, or Google Cloud Platform
- 1+ years of experience working with large code bases in a team
environment
- 1+ years of experience with distributed file systems or
multi-node database paradigms
- Contributed to open source ML software
- 1+ years of experience building production-ready data pipelines
that feed ML models At this time, Capital One will not sponsor a
new applicant for employment authorization for this position.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, race, color, age, national origin, religion,
physical and mental disability, genetic information, marital
status, sexual orientation, gender identity/assignment,
citizenship, pregnancy or maternity, protected veteran status, or
any other status prohibited by applicable national, 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-###-#### 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, Richmond , Machine Learning Engineer, Other , Richmond, Virginia
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